{"id":646,"date":"2025-02-17T10:22:05","date_gmt":"2025-02-17T10:22:05","guid":{"rendered":"https:\/\/www.9senses.ai\/?page_id=646"},"modified":"2026-08-05T15:03:39","modified_gmt":"2026-08-05T15:03:39","slug":"about-9senses","status":"publish","type":"page","link":"https:\/\/www.9senses.ai\/de\/about-9senses\/","title":{"rendered":"\u00dcber 9senses"},"content":{"rendered":"<div class=\"et_pb_section_0 et_pb_section et_section_regular et_block_section preset--group--divi-section--divi-box-shadow--default preset--group--divi-section--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_row_0 et_pb_row et_pb_row_3-4_1-4 et_block_row et_block_row_3-4_1-4 ns-hdr preset--group--divi-row--divi-box-shadow--default preset--group--divi-row--divi-sizing--h1k452m--default\">\n<div class=\"et_pb_column_0 et_pb_column et_pb_column_3_4 et_block_column et_pb_css_mix_blend_mode_passthrough preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n\n\n\n<div class=\"et_pb_text_0 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module preset--group--divi-text--divi-box-shadow--default preset--module--divi-text--default\"><div class=\"et_pb_text_inner\"><h4>Who we are - what we do<\/h4>\n<\/div><\/div>\n\n<div class=\"et_pb_text_1 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module preset--group--divi-text--divi-box-shadow--default preset--module--divi-text--default\"><div class=\"et_pb_text_inner\"><h1 style=\"text-align: left;\">About 9senses<\/h1>\n<\/div><\/div>\n\n<div class=\"et_pb_text_2 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module preset--group--divi-text--divi-box-shadow--default preset--module--divi-text--default\"><div class=\"et_pb_text_inner\"><p>9senses was founded by a group of AI veterans who want to provide solid services in an area where many offers are present, and where customers often lack the experience to decide about their validity. We are vendor-independent and able to clearly determine what AI can and cannot <a href=\"\/ai-ethics-and-governance\/\">(or should not)<\/a> do.<\/p>\n<p>Our objective is to help businesses and society alike to adapt to Artificial Intelligence, with deep insights, and no dependency on any vendor.<\/p>\n<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_1 et_pb_column et_pb_column_1_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_code_0 et_pb_code et_pb_module preset--group--divi-code--divi-box-shadow--default\"><div class=\"et_pb_code_inner\"><div class=\"ns-vmap-editor-note\" style=\"position:relative;width:100%;overflow:hidden;aspect-ratio:5\/4;max-height:230px;\"><div style=\"position:absolute;inset:0;display:flex;align-items:center;justify-content:center;pointer-events:none\"><div style=\"padding:10px 12px;border:1px dashed rgba(170,180,205,.55);border-radius:6px;color:#8a93a6;font:600 12px\/1.4 sans-serif;background:rgba(8,13,25,.46)\"><div style=\"margin-bottom:6px\">Vector map \u2014 small<\/div><code style=\"display:inline-block;padding:3px 6px;border-radius:4px;background:rgba(127,140,170,.12);color:inherit\"><div class=\"ns-vmap-editor-note\" style=\"position:relative;width:100%;overflow:hidden;aspect-ratio:5\/4;max-height:230px;\"><div style=\"position:absolute;inset:0;display:flex;align-items:center;justify-content:center;pointer-events:none\"><div style=\"padding:10px 12px;border:1px dashed rgba(170,180,205,.55);border-radius:6px;color:#8a93a6;font:600 12px\/1.4 sans-serif;background:rgba(8,13,25,.46)\"><div style=\"margin-bottom:6px\">Vector map \u2014 small<\/div><code style=\"display:inline-block;padding:3px 6px;border-radius:4px;background:rgba(127,140,170,.12);color:inherit\">[ninesenses_vectormap #3]<\/code><div style=\"margin-top:6px;font-weight:400\">Max height: 230px. Preview on the live page.<\/div><\/div><\/div><\/div><\/code><div style=\"margin-top:6px;font-weight:400\">Max height: 230px. Preview on the live page.<\/div><\/div><\/div><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_1 et_pb_section et_section_regular et_block_section ns-prose preset--group--divi-section--divi-box-shadow--default preset--group--divi-section--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_row_1 et_pb_row et_block_row preset--group--divi-row--divi-box-shadow--default preset--group--divi-row--divi-sizing--h1k452m--default\" id=\"team\">\n<div class=\"et_pb_column_2 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_code_1 et_pb_code et_pb_module preset--group--divi-code--divi-box-shadow--default\"><div class=\"et_pb_code_inner\"><div class=\"nsp-frame\"><div class=\"nsp-frame-head\"><h2>Our Team<\/h2><p>Meet a selection of our highly experienced team members. And: if you would like to become part of our growing practice, have a look at our <a href=\"\/jobs\">job openings<\/a>.<\/p><\/div><div class=\"nsp-carousel-wrap\" data-base-width=\"210\" data-loop=\"1\"><button type=\"button\" class=\"nsp-nav nsp-prev\" aria-label=\"Previous\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x34;<\/span><\/button><div class=\"nsp-carousel\">\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Alona Liuzniak\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/alona\/\"><img decoding=\"async\" width=\"266\" height=\"300\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2025\/05\/alona-266x300.png\" class=\"nsp-card-photo\" alt=\"Alona Liuzniak\" loading=\"lazy\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/alona\/\">Alona Liuzniak<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/nlp\" title=\"Natural Language Processing\" aria-label=\"Natural Language Processing\">NLP<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/customer-interaction\/\" title=\"Customer Interaction\" aria-label=\"Customer Interaction\">Customer Interaction<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/alona\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Alona ist Expertin f\u00fcr generative KI unter Verwendung nat\u00fcrlicher Sprachverarbeitung. Mit ihrem fundierten Wissen in den Bereichen maschinelles Lernen und Bildverarbeitung konzentriert sie sich derzeit haupts\u00e4chlich auf die Bereitstellung von verantwortungsvollen und erkl\u00e4rbaren Chatbot-L\u00f6sungen.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/alona\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Peter Gemeiner\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/peter\/\"><img decoding=\"async\" width=\"300\" height=\"280\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2025\/03\/Peter-Gemeiner-smaller-300x280.png\" class=\"nsp-card-photo\" alt=\"Peter Gemeiner\" loading=\"lazy\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/peter\/\">Peter Gemeiner<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/control-and-automation\" title=\"Automation\" aria-label=\"Automation\">Automation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/peter\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Peter ist ein versierter Experte mit fundierten Kenntnissen in den Bereichen maschinelles Lernen, Datenwissenschaft und Softwareentwicklung. Er hat an der Technischen Universit\u00e4t Wien promoviert und verf\u00fcgt \u00fcber Fachkenntnisse in verschiedenen Bereichen, u.a. k\u00fcnstliche Intelligenz, Cloud Computing.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/peter\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Fatima Ahmedii\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/fatima\/\"><img decoding=\"async\" class=\"nsp-card-photo nsp-card-photo--placeholder\" src=\"data:image\/svg+xml;charset=utf8,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20317%20317%22%20role%3D%22img%22%20aria-hidden%3D%22true%22%3E%3Cdefs%3E%3ClinearGradient%20id%3D%22bg%22%20x1%3D%220%22%20y1%3D%220%22%20x2%3D%221%22%20y2%3D%221%22%3E%3Cstop%20offset%3D%220%22%20stop-color%3D%22%2300091e%22%2F%3E%3Cstop%20offset%3D%221%22%20stop-color%3D%22%23141d33%22%2F%3E%3C%2FlinearGradient%3E%3CradialGradient%20id%3D%22halo%22%20cx%3D%2250%25%22%20cy%3D%2242%25%22%20r%3D%2262%25%22%3E%3Cstop%20offset%3D%220%22%20stop-color%3D%22%23cfcfcf%22%20stop-opacity%3D%22.26%22%2F%3E%3Cstop%20offset%3D%22.55%22%20stop-color%3D%22%2333405f%22%20stop-opacity%3D%22.18%22%2F%3E%3Cstop%20offset%3D%221%22%20stop-color%3D%22%2300091e%22%20stop-opacity%3D%220%22%2F%3E%3C%2FradialGradient%3E%3Cfilter%20id%3D%22blur%22%3E%3CfeGaussianBlur%20stdDeviation%3D%2210%22%2F%3E%3C%2Ffilter%3E%3C%2Fdefs%3E%3Crect%20width%3D%22317%22%20height%3D%22317%22%20fill%3D%22url%28%23bg%29%22%2F%3E%3Crect%20width%3D%22317%22%20height%3D%22317%22%20fill%3D%22url%28%23halo%29%22%2F%3E%3Cg%20filter%3D%22url%28%23blur%29%22%20opacity%3D%22.95%22%3E%3Cellipse%20cx%3D%2289%22%20cy%3D%22214%22%20rx%3D%2292%22%20ry%3D%2237%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.23%22%2F%3E%3Cellipse%20cx%3D%22222%22%20cy%3D%22226%22%20rx%3D%22102%22%20ry%3D%2243%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.19%22%2F%3E%3Cellipse%20cx%3D%22164%22%20cy%3D%22192%22%20rx%3D%2276%22%20ry%3D%2230%22%20fill%3D%22%23ffffff%22%20opacity%3D%22.10%22%2F%3E%3C%2Fg%3E%3Crect%20x%3D%2280%22%20y%3D%2272%22%20width%3D%22157%22%20height%3D%22157%22%20rx%3D%226%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.10%22%2F%3E%3Crect%20x%3D%2284%22%20y%3D%2276%22%20width%3D%22149%22%20height%3D%22149%22%20rx%3D%224%22%20fill%3D%22none%22%20stroke%3D%22%23cfcfcf%22%20stroke-opacity%3D%22.34%22%20stroke-width%3D%221.4%22%2F%3E%3Cpath%20d%3D%22M94%20204%20C130%20167%2C%20188%20167%2C%20224%20204%22%20fill%3D%22none%22%20stroke%3D%22%23cfcfcf%22%20stroke-opacity%3D%22.18%22%20stroke-width%3D%222%22%2F%3E%3Ctext%20x%3D%22158.5%22%20y%3D%22161%22%20text-anchor%3D%22middle%22%20dominant-baseline%3D%22middle%22%20font-family%3D%22Courier%20New%2C%20Courier%2C%20monospace%22%20font-size%3D%2270%22%20font-weight%3D%22700%22%20letter-spacing%3D%222%22%20fill%3D%22%23d3d3d3%22%20fill-opacity%3D%22.90%22%3EFA%3C%2Ftext%3E%3Crect%20x%3D%22103%22%20y%3D%22190%22%20width%3D%22111%22%20height%3D%223%22%20rx%3D%221.5%22%20fill%3D%22%232ea3f2%22%20opacity%3D%22.65%22%2F%3E%3C%2Fsvg%3E\" alt=\"\"><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/fatima\/\">Fatima Ahmedii<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/fatima\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Fatima ist eine echte Expertin f\u00fcr maschinelles Lernen und Bildverarbeitung. Sie verf\u00fcgt \u00fcber fundierte Kenntnisse in der Python-Entwicklung und anderen Programmiersprachen (u.a. Java). Ihre Kernkompetenz liegt in der Konzipierung von hybriden L\u00f6sungen, die KI mit solider Programmierung verbinden.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/fatima\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Juliette Schuster\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/juliette\/\"><img decoding=\"async\" width=\"216\" height=\"300\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/juliette-216x300.png\" class=\"nsp-card-photo\" alt=\"Juliette Schuster\" loading=\"lazy\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/juliette\/\">Juliette Schuster<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><span class=\"nsp-chip-text\" title=\"Human-Technology Interaction\" aria-label=\"Human-Technology Interaction\">Human-Technology Interaction<\/span><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/governance-and-ethics\" title=\"Governance\" aria-label=\"Governance\">Governance<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/ai-strategy\" title=\"AI Strategy\" aria-label=\"AI Strategy\">Strategy<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/governance-and-ethics\" title=\"Ethics\" aria-label=\"Ethics\">Ethics<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/juliette\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Juliette spezialisiert sich auf die Auswirkungen von KI auf Organisationen und die Menschen, die damit arbeiten. Auf Grundlage ihrer Berufserfahrung im Personalwesen sowie ihres B.Sc. in Psychologie untersucht sie, wie KI Arbeitsplatzdynamiken und Entscheidungsprozesse beeinflusst.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/juliette\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Johannes Kunz\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/johannes-2\/\"><img decoding=\"async\" width=\"226\" height=\"300\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/hannes-226x300.jpg\" class=\"nsp-card-photo\" alt=\"Johannes Kunz\" loading=\"lazy\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/hannes-226x300.jpg 226w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/hannes-9x12.jpg 9w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/hannes.jpg 400w\" sizes=\"(max-width: 226px) 100vw, 226px\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/johannes-2\/\">Johannes Kunz<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/ai-strategy\" title=\"AI Strategy\" aria-label=\"AI Strategy\">Strategy<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/consulting\" title=\"AI Transformation\" aria-label=\"AI Transformation\">AI Transformation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/nlp\" title=\"Natural Language Processing\" aria-label=\"Natural Language Processing\">NLP<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/johannes-2\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Mit mehr als 20 Jahren Erfahrung im Bereich der k\u00fcnstlichen Intelligenz \u2013 von strategischen Fragen bis hin zum Software- und Hardware-Design \u2013 bringt Johannes mehr mit als die meisten Experten. Er hat die gesamte Entwicklung der KI in den letzten Jahrzehnten miterlebt und wei\u00df, was (un)m\u00f6glich ist.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/johannes-2\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Alex Schmitz\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/alex\/\"><img decoding=\"async\" class=\"nsp-card-photo nsp-card-photo--placeholder\" src=\"data:image\/svg+xml;charset=utf8,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20317%20317%22%20role%3D%22img%22%20aria-hidden%3D%22true%22%3E%3Cdefs%3E%3ClinearGradient%20id%3D%22bg%22%20x1%3D%220%22%20y1%3D%220%22%20x2%3D%221%22%20y2%3D%221%22%3E%3Cstop%20offset%3D%220%22%20stop-color%3D%22%2300091e%22%2F%3E%3Cstop%20offset%3D%221%22%20stop-color%3D%22%23141d33%22%2F%3E%3C%2FlinearGradient%3E%3CradialGradient%20id%3D%22halo%22%20cx%3D%2250%25%22%20cy%3D%2242%25%22%20r%3D%2262%25%22%3E%3Cstop%20offset%3D%220%22%20stop-color%3D%22%23cfcfcf%22%20stop-opacity%3D%22.26%22%2F%3E%3Cstop%20offset%3D%22.55%22%20stop-color%3D%22%2333405f%22%20stop-opacity%3D%22.18%22%2F%3E%3Cstop%20offset%3D%221%22%20stop-color%3D%22%2300091e%22%20stop-opacity%3D%220%22%2F%3E%3C%2FradialGradient%3E%3Cfilter%20id%3D%22blur%22%3E%3CfeGaussianBlur%20stdDeviation%3D%2210%22%2F%3E%3C%2Ffilter%3E%3C%2Fdefs%3E%3Crect%20width%3D%22317%22%20height%3D%22317%22%20fill%3D%22url%28%23bg%29%22%2F%3E%3Crect%20width%3D%22317%22%20height%3D%22317%22%20fill%3D%22url%28%23halo%29%22%2F%3E%3Cg%20filter%3D%22url%28%23blur%29%22%20opacity%3D%22.95%22%3E%3Cellipse%20cx%3D%2289%22%20cy%3D%22214%22%20rx%3D%2292%22%20ry%3D%2237%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.23%22%2F%3E%3Cellipse%20cx%3D%22222%22%20cy%3D%22226%22%20rx%3D%22102%22%20ry%3D%2243%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.19%22%2F%3E%3Cellipse%20cx%3D%22164%22%20cy%3D%22192%22%20rx%3D%2276%22%20ry%3D%2230%22%20fill%3D%22%23ffffff%22%20opacity%3D%22.10%22%2F%3E%3C%2Fg%3E%3Crect%20x%3D%2280%22%20y%3D%2272%22%20width%3D%22157%22%20height%3D%22157%22%20rx%3D%226%22%20fill%3D%22%23cfcfcf%22%20opacity%3D%22.10%22%2F%3E%3Crect%20x%3D%2284%22%20y%3D%2276%22%20width%3D%22149%22%20height%3D%22149%22%20rx%3D%224%22%20fill%3D%22none%22%20stroke%3D%22%23cfcfcf%22%20stroke-opacity%3D%22.34%22%20stroke-width%3D%221.4%22%2F%3E%3Cpath%20d%3D%22M94%20204%20C130%20167%2C%20188%20167%2C%20224%20204%22%20fill%3D%22none%22%20stroke%3D%22%23cfcfcf%22%20stroke-opacity%3D%22.18%22%20stroke-width%3D%222%22%2F%3E%3Ctext%20x%3D%22158.5%22%20y%3D%22161%22%20text-anchor%3D%22middle%22%20dominant-baseline%3D%22middle%22%20font-family%3D%22Courier%20New%2C%20Courier%2C%20monospace%22%20font-size%3D%2270%22%20font-weight%3D%22700%22%20letter-spacing%3D%222%22%20fill%3D%22%23d3d3d3%22%20fill-opacity%3D%22.90%22%3EAS%3C%2Ftext%3E%3Crect%20x%3D%22103%22%20y%3D%22190%22%20width%3D%22111%22%20height%3D%223%22%20rx%3D%221.5%22%20fill%3D%22%232ea3f2%22%20opacity%3D%22.65%22%2F%3E%3C%2Fsvg%3E\" alt=\"\"><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/alex\/\">Alex Schmitz<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/data-and-knowledge-management\/\" title=\"Data Warehouse\" aria-label=\"Data Warehouse\">Data Warehouse<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/alex\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Mit mehr als 25 Jahren Erfahrung in der Informatik und \u00fcber 15 Jahren im Bereich des maschinellen Lernens ist Alexander ein versierter Systemarchitekt und ein ML-Experte, der sich mit nahezu allen Frameworks bestens auskennt, inklusive der Governance Aspekte.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/alex\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Sophia Wagner\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/sophia\/\"><img decoding=\"async\" width=\"300\" height=\"272\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Selfie-300x272.png\" class=\"nsp-card-photo\" alt=\"Sophia Wagner\" loading=\"lazy\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/sophia\/\">Sophia Wagner<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/nlp\" title=\"Natural Language Processing\" aria-label=\"Natural Language Processing\">NLP<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/machine-learning\" title=\"Machine Learning\" aria-label=\"Machine Learning\">ML<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/control-and-automation\" title=\"Automation\" aria-label=\"Automation\">Automation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/consulting\" title=\"AI Transformation\" aria-label=\"AI Transformation\">AI Transformation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/automation-and-control\" title=\"Infrastructure Management\" aria-label=\"Infrastructure Management\">Infrastructure<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/sophia\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>KI-Ingenieurin mit wissenschaftlichem Hintergrund in Mathematik, spezialisiert auf gro\u00dfe Sprachmodelle (LLMs), semantische Suche und RAG-Systeme. Ihre Leidenschaft gilt der Umsetzung komplexer Informationen in praktische KI-L\u00f6sungen.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/sophia\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"nsp-card nsp-card--person\" aria-label=\"Valentino Strebel\">\n\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-photowrap\" href=\"https:\/\/www.9senses.ai\/de\/valentino\/\"><img decoding=\"async\" width=\"211\" height=\"300\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/valentinobusiness_portrait-211x300-1.jpg\" class=\"nsp-card-photo\" alt=\"Valentino Strebel\" loading=\"lazy\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/valentinobusiness_portrait-211x300-1.jpg 211w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/valentinobusiness_portrait-211x300-1-8x12.jpg 8w\" sizes=\"(max-width: 211px) 100vw, 211px\" \/><\/a>\n\t\t\t\t\t\t\t\t<h3 class=\"nsp-card-title\"><a class=\"nsp-card-titlelink\" href=\"https:\/\/www.9senses.ai\/de\/valentino\/\">Valentino Strebel<\/a><\/h3>\n\t\t\t\t\t\t\t\t\t<ul class=\"nsp-card-caps\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/vision\" title=\"Computer Vision\" aria-label=\"Computer Vision\">Vision<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><span class=\"nsp-chip-text\" title=\"Human-Technology Interaction\" aria-label=\"Human-Technology Interaction\">Human-Technology Interaction<\/span><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/nlp\" title=\"Natural Language Processing\" aria-label=\"Natural Language Processing\">NLP<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/consulting\" title=\"AI Transformation\" aria-label=\"AI Transformation\">AI Transformation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\"><a class=\"nsp-chip-link\" href=\"\/control-and-automation\" title=\"Automation\" aria-label=\"Automation\">Automation<\/a><\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"nsp-card-excerpt-link\" href=\"https:\/\/www.9senses.ai\/de\/valentino\/\" tabindex=\"-1\"><span class=\"nsp-card-excerpt\" data-no-translation data-no-dynamic-translation>Valentino ist spezialisiert auf Transformationsberatung, Prozessmanagement, ERP-Implementierung und Softwareprojekte und verbindet dabei technisches Fachwissen mit ausgepr\u00e4gtem organisatorischem Verst\u00e4ndnis. Ein besonderer Schwerpunkt liegt im Bereich IT Operations.<\/span><\/a>\n\t\t\t\t\t\t\t\t<a class=\"nsp-card-more\" href=\"https:\/\/www.9senses.ai\/de\/valentino\/\">read more\u2026<\/a>\n\t\t\t<\/div>\n\t\t\t<\/div><button type=\"button\" class=\"nsp-nav nsp-next\" aria-label=\"Next\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x35;<\/span><\/button><\/div><script>(function(){\n\t\t\tif (!window.nspComputeLayout) {\n\t\t\t\twindow.NSP_BASE_CARD_WIDTH = 240;\n\t\t\t\twindow.nspIsFluidWidth = function(){ return window.innerWidth > 640; };\n\t\t\t\twindow.nspComputeLayout = function(available, gap, totalCards, baseWidth){\n\t\t\t\t\tvar BASE = baseWidth || window.NSP_BASE_CARD_WIDTH;\n\t\t\t\t\tavailable = Math.max(0, available || 0);\n\t\t\t\t\tgap = Math.max(0, gap || 0);\n\t\t\t\t\ttotalCards = Math.max(0, totalCards || 0);\n\t\t\t\t\tif (!totalCards){\n\t\t\t\t\t\treturn { count: 0, width: BASE, center: true };\n\t\t\t\t\t}\n\t\t\t\t\tvar per = BASE + gap;\n\t\t\t\t\tvar baseCount = Math.max(1, Math.floor((available + gap) \/ per));\n\t\t\t\t\tvar used = baseCount * BASE + (baseCount - 1) * gap;\n\t\t\t\t\tvar remainder = available - used;\n\t\t\t\t\t\/\/ Only create an extra visible slot when there is actually another card to fill it.\n\t\t\t\t\t\/\/ If exactly the base-width row count is present, distribute those cards evenly\n\t\t\t\t\t\/\/ across the row instead of leaving them beside a phantom extra slot.\n\t\t\t\t\tvar fullCount = (totalCards > baseCount && remainder >= (2 \/ 3) * BASE) ? baseCount + 1 : baseCount;\n\t\t\t\t\tfullCount = Math.max(1, fullCount);\n\t\t\t\t\tvar fullWidth = (available - (fullCount - 1) * gap) \/ fullCount;\n\t\t\t\t\tif (!isFinite(fullWidth) || fullWidth <= 0){ fullWidth = BASE; }\n\n\t\t\t\t\t\/\/ One or two cards should never grow just because the row is wide.\n\t\t\t\t\t\/\/ They keep the base width, sit at the left, and leave the rest of the row empty.\n\t\t\t\t\tif (totalCards < 3){\n\t\t\t\t\t\tvar smallMax = (available - (totalCards - 1) * gap) \/ totalCards;\n\t\t\t\t\t\tvar smallWidth = (isFinite(smallMax) && smallMax > 0) ? Math.min(BASE, smallMax) : BASE;\n\t\t\t\t\t\treturn { count: totalCards, width: smallWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\t\/\/ If there are fewer cards than a full row would hold, keep the full-row\n\t\t\t\t\t\/\/ card width rather than stretching those few across the whole row, and\n\t\t\t\t\t\/\/ leave the remaining slots empty. Left-aligned, as the master grid is.\n\t\t\t\t\tif (totalCards < fullCount){\n\t\t\t\t\t\treturn { count: totalCards, width: fullWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\tvar count = Math.min(fullCount, totalCards);\n\t\t\t\t\treturn { count: count, width: fullWidth, center: false };\n\t\t\t\t};\n\t\t\t\t\/\/ Centre the chevrons on the media block of a card rather than on\n\t\t\t\t\/\/ the whole card: on people cards that is the square photo\n\t\t\t\t\/\/ (whose height tracks the fluid card width, so it cannot be\n\t\t\t\t\/\/ expressed in CSS), on project cards the icon block. Published\n\t\t\t\t\/\/ as a custom property the stylesheet reads.\n\t\t\t\twindow.nspTrackPadX = function(track){\n\t\t\t\t\tvar cs = window.getComputedStyle(track);\n\t\t\t\t\treturn (parseFloat(cs.paddingLeft) || 0) + (parseFloat(cs.paddingRight) || 0);\n\t\t\t\t};\n\t\t\t\twindow.nspSyncNav = function(wrap){\n\t\t\t\t\t\/\/ People cards anchor on the photo, which is the visual mass of\n\t\t\t\t\t\/\/ the card. Project cards have no photo -- only a small icon\n\t\t\t\t\t\/\/ at the top -- so they anchor on the card panel itself and\n\t\t\t\t\t\/\/ the arrows land on its vertical centre. Measuring against\n\t\t\t\t\t\/\/ the wrap in viewport coordinates absorbs the track padding\n\t\t\t\t\t\/\/ and card margins without restating any of them here.\n\t\t\t\t\tvar media = wrap.querySelector(\".nsp-card-photo\")\n\t\t\t\t\t\t|| wrap.querySelector(\".nsp-card\");\n\t\t\t\t\tif (!media){ return; }\n\t\t\t\t\tvar r = media.getBoundingClientRect();\n\t\t\t\t\tif (!r.height){ return; }\n\t\t\t\t\tvar w = wrap.getBoundingClientRect();\n\t\t\t\t\twrap.style.setProperty(\"--nsp-nav-top\", ((r.top - w.top) + r.height \/ 2) + \"px\");\n\t\t\t\t};\n\t\t\t}\n\t\t\tvar wrap = document.currentScript.previousElementSibling;\n\t\t\tif(!wrap){ return; }\n\t\t\t\/\/ The frame carries the visible panel, so it has to be revealed\n\t\t\t\/\/ together with the wrap -- otherwise an empty framed box paints\n\t\t\t\/\/ before the cards have been sized into it.\n\t\t\tfunction reveal(w){\n\t\t\t\tw.style.visibility = \"visible\";\n\t\t\t\tvar f = w.parentNode;\n\t\t\t\tif (f && f.classList && f.classList.contains(\"nsp-frame\")){ f.style.visibility = \"visible\"; }\n\t\t\t}\n\t\t\tvar baseWidth = parseInt(wrap.getAttribute(\"data-base-width\"), 10) || window.NSP_BASE_CARD_WIDTH;\n\t\t\tvar track = wrap.querySelector(\".nsp-carousel\");\n\t\t\tvar cards = track ? track.querySelectorAll(\".nsp-card\") : [];\n\t\t\tif(!track || !cards.length){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\/\/ Read from the stylesheet rather than restating it: a hard-coded copy\n\t\t\t\/\/ here is exactly how the gutter drifted from the CSS before.\n\t\t\tvar gap = parseFloat(window.getComputedStyle(track).columnGap) || 24;\n\t\t\tif (!window.nspIsFluidWidth()) {\n\t\t\t\t\/\/ Mobile: unchanged -- fixed per-card width (CSS 82vw), just avoid a partial\n\t\t\t\t\/\/ card peeking out at the wrap edge.\n\t\t\t\tvar cardW = cards[0].getBoundingClientRect().width;\n\t\t\t\tif(!cardW){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\t\/\/ clientWidth is the PADDING box, so the track padding has to come\n\t\t\t\t\/\/ off before this is the room the cards actually get.\n\t\t\t\tvar available0 = track.clientWidth - window.nspTrackPadX(track);\n\t\t\t\tvar fitCount = Math.max(1, Math.floor((available0 + gap) \/ (cardW + gap)));\n\t\t\t\tvar count0 = Math.min(fitCount, cards.length);\n\t\t\t\tvar needed0 = count0 * cardW + (count0 - 1) * gap;\n\t\t\t\tvar ws0 = window.getComputedStyle(wrap);\n\t\t\t\tvar padX0 = (parseFloat(ws0.paddingLeft) || 0) + (parseFloat(ws0.paddingRight) || 0);\n\t\t\t\tvar target0 = needed0 + window.nspTrackPadX(track) + (ws0.boxSizing === \"border-box\" ? padX0 : 0);\n\t\t\t\twrap.style.maxWidth = Math.ceil(target0) + \"px\";\n\t\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t\/\/ Desktop\/tablet: fluid card width, filling the row exactly either way.\n\t\t\t\/\/ clientWidth is the PADDING box -- take the track padding off it.\n\t\t\tvar available = track.clientWidth - window.nspTrackPadX(track);\n\t\t\tvar layout = window.nspComputeLayout(available, gap, cards.length, baseWidth);\n\t\t\tfor (var i = 0; i < cards.length; i++){ cards[i].style.flex = \"0 0 \" + layout.width + \"px\"; }\n\t\t\tif (layout.center) {\n\t\t\t\tvar totalW = layout.count * layout.width + (layout.count - 1) * gap;\n\t\t\t\twrap.style.maxWidth = Math.ceil(totalW + window.nspTrackPadX(track)) + \"px\";\n\t\t\t\twrap.style.marginLeft = \"auto\";\n\t\t\t\twrap.style.marginRight = \"auto\";\n\t\t\t}\n\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t})();<\/script><\/div><noscript><style>.nsp-carousel-wrap,.nsp-frame{visibility:visible !important;}<\/style><\/noscript><div class=\"nsp-popups\" hidden><\/div><div class=\"nsp-overlay\" id=\"nsp-overlay\" role=\"dialog\" aria-modal=\"true\"><\/div> <\/div><\/div>\n\n<div class=\"et_pb_text_3 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module preset--group--divi-text--divi-box-shadow--default preset--module--divi-text--default\" id=\"office\"><div class=\"et_pb_text_inner\"><h2>Our Offices<\/h2>\n<\/div><\/div>\n\n<div class=\"et_pb_text_4 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module preset--group--divi-text--divi-box-shadow--default preset--module--divi-text--default\"><div class=\"et_pb_text_inner\"><p>9senses has a global reach. We started in <a href=\"#contact?Switzerland\">Switzerland<\/a> and are slowly expanding our footprint. 2026 additions are: <a href=\"#contact?Germany\">Germany<\/a>, the <a href=\"#contact?United%20Kingdom\">UK<\/a>, <a href=\"#contact?North%20America\">North America<\/a>, and <a href=\"#contact?Oceania\">Oceania<\/a>. And since offices are so 20th century, we have made our office map a bit more fun to look at. Play around, watch the planets move, check out the moon, or catch an office tile and click it.<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_2 et_pb_row et_flex_row preset--group--divi-row--divi-box-shadow--default preset--group--divi-row--divi-sizing--h1k452m--default\">\n<div class=\"et_pb_column_3 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_code_2 et_pb_code et_pb_module preset--group--divi-code--divi-box-shadow--default\"><div class=\"et_pb_code_inner\">\t\t<div class=\"orrery-root\"\n\t\t\tid=\"orrery-a62113c2-ea5e-4e99-91d6-1936990de39d\"\n\t\t\tstyle=\"width:100%;height:560px;\"\n\t\t\tdata-orrery=\"{&quot;speed&quot;:0.05,&quot;moon&quot;:true,&quot;clouds&quot;:true,&quot;stars&quot;:true,&quot;orbits&quot;:true,&quot;labels&quot;:true,&quot;controls&quot;:true,&quot;view&quot;:&quot;earth&quot;,&quot;autorotate&quot;:true,&quot;offices&quot;:[{&quot;region&quot;:&quot;Switzerland&quot;,&quot;city&quot;:&quot;Zurich&quot;,&quot;phone&quot;:&quot;+41 44 500 43 91&quot;,&quot;lat&quot;:47.3769,&quot;lng&quot;:8.5417},{&quot;region&quot;:&quot;Germany&quot;,&quot;city&quot;:&quot;Offenburg&quot;,&quot;phone&quot;:&quot;+49 7808 91 38-280&quot;,&quot;lat&quot;:48.4709,&quot;lng&quot;:7.9415},{&quot;region&quot;:&quot;UK&quot;,&quot;city&quot;:&quot;Bath&quot;,&quot;phone&quot;:&quot;+44 1225&quot;,&quot;lat&quot;:51.3811,&quot;lng&quot;:-2.359},{&quot;region&quot;:&quot;North America&quot;,&quot;city&quot;:&quot;Toronto&quot;,&quot;phone&quot;:&quot;+1 437 837 3730&quot;,&quot;lat&quot;:43.6532,&quot;lng&quot;:-79.3832},{&quot;region&quot;:&quot;Oceania&quot;,&quot;city&quot;:&quot;Auckland&quot;,&quot;phone&quot;:&quot;+64 9 802 5273&quot;,&quot;lat&quot;:-36.8485,&quot;lng&quot;:174.7633}],&quot;contact&quot;:&quot;#contact&quot;}\">\n\t\t\t<div class=\"orrery-canvas-host\" aria-hidden=\"true\"><\/div>\n\t\t\t<noscript>\n\t\t\t\t<p class=\"orrery-noscript\">This 3D orrery needs JavaScript enabled to run.<\/p>\n\t\t\t<\/noscript>\n\t\t<\/div>\n\t\t<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_3 et_pb_row et_flex_row preset--group--divi-row--divi-box-shadow--default preset--group--divi-row--divi-sizing--h1k452m--default\">\n<div class=\"et_pb_column_4 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_code_3 et_pb_code et_pb_module preset--group--divi-code--divi-box-shadow--default\"><div class=\"et_pb_code_inner\"><div class=\"nsp-frame\"><div class=\"nsp-frame-head\"><h2>Featured Projects<\/h2><\/div><div class=\"nsp-carousel-wrap\" data-base-width=\"240\" data-loop=\"1\"><button type=\"button\" class=\"nsp-nav nsp-prev\" aria-label=\"Previous\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x34;<\/span><\/button><div class=\"nsp-carousel\">\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"3\" aria-label=\"RAG-driven Legal Chatbot\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-section\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">RAG-driven Legal Chatbot<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">A small-to-medium language model reliably answering German legal questions based on a strong RAG pipeline.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"7\" aria-label=\"Generative AI Audit Framework\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Generative AI Audit Framework<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Development of a structured Generative AI audit framework. This included establishing a methodology for Level 1 and Level 2 GenAI audits<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"10\" aria-label=\"Facility Management Process Digitalization\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe035;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Facility Management Process Digitalization<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Transformation and standardization of international facility management processes through the introduction of scalable structures.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"11\" aria-label=\"ERP\/CRM Product Development\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe00d;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">ERP\/CRM Product Development<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Development and implementation of a modular ERP\/CRM system to digitalize central business processes.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"12\" aria-label=\"Intelligent Data Retrieval Agent\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Intelligent Data Retrieval Agent<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Production-ready AI retrieval system using LLMs and semantic search to transform fragmented data into reliable, searchable knowledge.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"13\" aria-label=\"Visual Search Recommendations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-socks\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Search Recommendations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">eCommmerce plugin that enables searching for visually similar products, helping customers to find and compare multiple related items.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"14\" aria-label=\"Visual Assistance for Seniors\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-glasses\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Assistance for Seniors<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Visual Assistance App: enabling visual assistance for seniors by helping position determination using Computer Vision and Deep Learning.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"1\" aria-label=\"Electrical Switch Monitor\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-toggle-on\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Electrical Switch Monitor<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Public transportation: using AI-driven vision to monitor old-fashioned electrical relays and also to evaluate potential failures for predictive maintenance.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"5\" aria-label=\"Hydropower Plant Operations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Hydropower Plant Operations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Create a control and monitoring solution for all plant operations, including predictive maintenance logic and intrusion mon\u00aditoring.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"2\" aria-label=\"Customer Interaction Analysis\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Customer Interaction Analysis<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">SaaS project platform: the objective was to evaluate dialogue quality using an AI model to ensure timely intervention and customer care.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"6\" aria-label=\"Motion-sensitive wearables\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-shirt\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Motion-sensitive wearables<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Wearable fabric-based devices with embedded microcontrollers and sensitivity for motion, heartbeat, body temperature and sweat detection.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"4\" aria-label=\"IT Operations Automation\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-network-wired\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">IT Operations Automation<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Financial Services: develop strategy and business cases to introduce automation and AI into the IT operations environment.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t<\/div><button type=\"button\" class=\"nsp-nav nsp-next\" aria-label=\"Next\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x35;<\/span><\/button><\/div><script>(function(){\n\t\t\tif (!window.nspComputeLayout) {\n\t\t\t\twindow.NSP_BASE_CARD_WIDTH = 240;\n\t\t\t\twindow.nspIsFluidWidth = function(){ return window.innerWidth > 640; };\n\t\t\t\twindow.nspComputeLayout = function(available, gap, totalCards, baseWidth){\n\t\t\t\t\tvar BASE = baseWidth || window.NSP_BASE_CARD_WIDTH;\n\t\t\t\t\tavailable = Math.max(0, available || 0);\n\t\t\t\t\tgap = Math.max(0, gap || 0);\n\t\t\t\t\ttotalCards = Math.max(0, totalCards || 0);\n\t\t\t\t\tif (!totalCards){\n\t\t\t\t\t\treturn { count: 0, width: BASE, center: true };\n\t\t\t\t\t}\n\t\t\t\t\tvar per = BASE + gap;\n\t\t\t\t\tvar baseCount = Math.max(1, Math.floor((available + gap) \/ per));\n\t\t\t\t\tvar used = baseCount * BASE + (baseCount - 1) * gap;\n\t\t\t\t\tvar remainder = available - used;\n\t\t\t\t\t\/\/ Only create an extra visible slot when there is actually another card to fill it.\n\t\t\t\t\t\/\/ If exactly the base-width row count is present, distribute those cards evenly\n\t\t\t\t\t\/\/ across the row instead of leaving them beside a phantom extra slot.\n\t\t\t\t\tvar fullCount = (totalCards > baseCount && remainder >= (2 \/ 3) * BASE) ? baseCount + 1 : baseCount;\n\t\t\t\t\tfullCount = Math.max(1, fullCount);\n\t\t\t\t\tvar fullWidth = (available - (fullCount - 1) * gap) \/ fullCount;\n\t\t\t\t\tif (!isFinite(fullWidth) || fullWidth <= 0){ fullWidth = BASE; }\n\n\t\t\t\t\t\/\/ One or two cards should never grow just because the row is wide.\n\t\t\t\t\t\/\/ They keep the base width, sit at the left, and leave the rest of the row empty.\n\t\t\t\t\tif (totalCards < 3){\n\t\t\t\t\t\tvar smallMax = (available - (totalCards - 1) * gap) \/ totalCards;\n\t\t\t\t\t\tvar smallWidth = (isFinite(smallMax) && smallMax > 0) ? Math.min(BASE, smallMax) : BASE;\n\t\t\t\t\t\treturn { count: totalCards, width: smallWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\t\/\/ If there are fewer cards than a full row would hold, keep the full-row\n\t\t\t\t\t\/\/ card width rather than stretching those few across the whole row, and\n\t\t\t\t\t\/\/ leave the remaining slots empty. Left-aligned, as the master grid is.\n\t\t\t\t\tif (totalCards < fullCount){\n\t\t\t\t\t\treturn { count: totalCards, width: fullWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\tvar count = Math.min(fullCount, totalCards);\n\t\t\t\t\treturn { count: count, width: fullWidth, center: false };\n\t\t\t\t};\n\t\t\t\t\/\/ Centre the chevrons on the media block of a card rather than on\n\t\t\t\t\/\/ the whole card: on people cards that is the square photo\n\t\t\t\t\/\/ (whose height tracks the fluid card width, so it cannot be\n\t\t\t\t\/\/ expressed in CSS), on project cards the icon block. Published\n\t\t\t\t\/\/ as a custom property the stylesheet reads.\n\t\t\t\twindow.nspTrackPadX = function(track){\n\t\t\t\t\tvar cs = window.getComputedStyle(track);\n\t\t\t\t\treturn (parseFloat(cs.paddingLeft) || 0) + (parseFloat(cs.paddingRight) || 0);\n\t\t\t\t};\n\t\t\t\twindow.nspSyncNav = function(wrap){\n\t\t\t\t\t\/\/ People cards anchor on the photo, which is the visual mass of\n\t\t\t\t\t\/\/ the card. Project cards have no photo -- only a small icon\n\t\t\t\t\t\/\/ at the top -- so they anchor on the card panel itself and\n\t\t\t\t\t\/\/ the arrows land on its vertical centre. Measuring against\n\t\t\t\t\t\/\/ the wrap in viewport coordinates absorbs the track padding\n\t\t\t\t\t\/\/ and card margins without restating any of them here.\n\t\t\t\t\tvar media = wrap.querySelector(\".nsp-card-photo\")\n\t\t\t\t\t\t|| wrap.querySelector(\".nsp-card\");\n\t\t\t\t\tif (!media){ return; }\n\t\t\t\t\tvar r = media.getBoundingClientRect();\n\t\t\t\t\tif (!r.height){ return; }\n\t\t\t\t\tvar w = wrap.getBoundingClientRect();\n\t\t\t\t\twrap.style.setProperty(\"--nsp-nav-top\", ((r.top - w.top) + r.height \/ 2) + \"px\");\n\t\t\t\t};\n\t\t\t}\n\t\t\tvar wrap = document.currentScript.previousElementSibling;\n\t\t\tif(!wrap){ return; }\n\t\t\t\/\/ The frame carries the visible panel, so it has to be revealed\n\t\t\t\/\/ together with the wrap -- otherwise an empty framed box paints\n\t\t\t\/\/ before the cards have been sized into it.\n\t\t\tfunction reveal(w){\n\t\t\t\tw.style.visibility = \"visible\";\n\t\t\t\tvar f = w.parentNode;\n\t\t\t\tif (f && f.classList && f.classList.contains(\"nsp-frame\")){ f.style.visibility = \"visible\"; }\n\t\t\t}\n\t\t\tvar baseWidth = parseInt(wrap.getAttribute(\"data-base-width\"), 10) || window.NSP_BASE_CARD_WIDTH;\n\t\t\tvar track = wrap.querySelector(\".nsp-carousel\");\n\t\t\tvar cards = track ? track.querySelectorAll(\".nsp-card\") : [];\n\t\t\tif(!track || !cards.length){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\/\/ Read from the stylesheet rather than restating it: a hard-coded copy\n\t\t\t\/\/ here is exactly how the gutter drifted from the CSS before.\n\t\t\tvar gap = parseFloat(window.getComputedStyle(track).columnGap) || 24;\n\t\t\tif (!window.nspIsFluidWidth()) {\n\t\t\t\t\/\/ Mobile: unchanged -- fixed per-card width (CSS 82vw), just avoid a partial\n\t\t\t\t\/\/ card peeking out at the wrap edge.\n\t\t\t\tvar cardW = cards[0].getBoundingClientRect().width;\n\t\t\t\tif(!cardW){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\t\/\/ clientWidth is the PADDING box, so the track padding has to come\n\t\t\t\t\/\/ off before this is the room the cards actually get.\n\t\t\t\tvar available0 = track.clientWidth - window.nspTrackPadX(track);\n\t\t\t\tvar fitCount = Math.max(1, Math.floor((available0 + gap) \/ (cardW + gap)));\n\t\t\t\tvar count0 = Math.min(fitCount, cards.length);\n\t\t\t\tvar needed0 = count0 * cardW + (count0 - 1) * gap;\n\t\t\t\tvar ws0 = window.getComputedStyle(wrap);\n\t\t\t\tvar padX0 = (parseFloat(ws0.paddingLeft) || 0) + (parseFloat(ws0.paddingRight) || 0);\n\t\t\t\tvar target0 = needed0 + window.nspTrackPadX(track) + (ws0.boxSizing === \"border-box\" ? padX0 : 0);\n\t\t\t\twrap.style.maxWidth = Math.ceil(target0) + \"px\";\n\t\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t\/\/ Desktop\/tablet: fluid card width, filling the row exactly either way.\n\t\t\t\/\/ clientWidth is the PADDING box -- take the track padding off it.\n\t\t\tvar available = track.clientWidth - window.nspTrackPadX(track);\n\t\t\tvar layout = window.nspComputeLayout(available, gap, cards.length, baseWidth);\n\t\t\tfor (var i = 0; i < cards.length; i++){ cards[i].style.flex = \"0 0 \" + layout.width + \"px\"; }\n\t\t\tif (layout.center) {\n\t\t\t\tvar totalW = layout.count * layout.width + (layout.count - 1) * gap;\n\t\t\t\twrap.style.maxWidth = Math.ceil(totalW + window.nspTrackPadX(track)) + \"px\";\n\t\t\t\twrap.style.marginLeft = \"auto\";\n\t\t\t\twrap.style.marginRight = \"auto\";\n\t\t\t}\n\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t})();<\/script><\/div><noscript><style>.nsp-carousel-wrap,.nsp-frame{visibility:visible !important;}<\/style><\/noscript><div class=\"nsp-popups\" hidden><template class=\"nsp-popup-tpl\" data-id=\"3\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-section\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">RAG-driven Legal Chatbot<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>An AI-supported RAG-Chatbot developed for legal and administrative workflows. Designed to support caseworkers in navigating complex regulations - currently focused on German Social Welfare - the system provides fast, contextual access to relevant legal information and assists in decision-making for applications and case management. The modular architecture allows seamless expansion into additional legal domains and regulatory frameworks.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"7\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Generative AI Audit Framework<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Development of a multidimensional Blackbox Chatbot Audit framework for evaluating chatbot user experience and business value in customer service environments. The audit methodology combines structured use-case testing with qualitative and quantitative evaluation dimensions, including answer quality, response speed, dialogue quality, and user interface assessment.<\/p>\n<p>The framework also incorporates hallucination testing and edge-case analysis to assess robustness and real-world usability. The project included extensive market and user-frustration research, methodology development, pilot implementation, and iterative testing and retesting phases. The resulting audit framework is used to evaluate chatbot performance, identify optimization potential, and assess user retention likelihood and overall business impact.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/governance-and-ethics\">Governance<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"10\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Facility Management Process Digitalization<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Supported the transformation and standardization of international facility management processes by designing scalable end-to-end process and service structures.<\/p>\n<p>The project included gathering and harmonizing requirements across multiple country organizations, translating business needs into digital process and system solutions, and coordinating international rollouts including SIT, UAT, training, and change management.<\/p>\n<p>Consistent process modeling and documentation using BPMN 2.0 and SAP Signavio helped establish sustainable governance, transparency, and operational efficiency.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image1-1024x768.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image1-980x735.png 980w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image1-480x360.png 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1024px, 100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>SAP Signavio, BPMN 2.0, ERP Systems, Digital Workflow Platforms, Interface Integration, SIT\/UAT, Requirements Management<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tHuman-Technology Interaction\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"11\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">ERP\/CRM Product Development<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Led the development and implementation of a modular ERP\/CRM system to digitalize central business processes.<\/p>\n<p>The project included end-to-end product ownership, requirements analysis, prioritization, and scaling of the system, including mobile solutions and extensions.<\/p>\n<p>Responsibilities also covered the management of cross-functional development teams, the establishment of testing, quality, and operations processes, and the introduction of ITIL-based change and incident structures. Governance, KPI, PMO, and documentation standards were developed to support sustainable product and project management, while product strategy and stakeholder alignment were managed at leadership level.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image2-1024x768.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image2-980x735.png 980w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/Image2-480x360.png 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1024px, 100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>ERP\/CRM Systems, Mobile Solutions, Agile Product Development, Requirements Management, UAT, ITIL, Change &amp; Incident Management, KPI\/PMO Structures, Stakeholder Management<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/data-and-knowledge-management\/\">Data Warehouse<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tHuman-Technology Interaction\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"12\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Intelligent Data Retrieval Agent<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Development of a production-ready retrieval agent for querying large, fragmented, and undocumented enterprise data repositories using large language models and semantic search. The solution transformed scattered legacy records into structured, searchable knowledge, enabling users to retrieve relevant information within seconds instead of manually searching across hundreds of documents.<\/p>\n<p>The project combined retrieval-augmented generation (RAG), vector search, and modern LLM technologies to deliver reliable, context-aware information retrieval. Designed with a modular architecture, the system supports scalability, maintainability, and future extensions while ensuring robust retrieval quality across heterogeneous data sources.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>AI Engineer<\/p>\n<p>Python \u2022 LangChain \u2022 OpenAI \u2022 Qdrant \u2022 Semantic Search \u2022 RAG \u2022 Streamlit<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"13\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Search Recommendations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For VisualSearch, the focus was on developing and deploying e-commerce plugins to enhance recommendation functionalities in web shops. The plugins were successfully launched in the store and happily adopted by customers, demonstrating their practical use in improving e-commerce experiences. Key elements included:<br \/>\n- computation of visual embeddings from appearances of e-commerce products<br \/>\n- building and maintaining a search index using these embeddings<br \/>\n- providing a cloud-based API for Shopware and Prestashop plugins<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"369\" height=\"455\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png 369w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-10x12.png 10w\" sizes=\"(max-width: 369px) 100vw, 369px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, leveraging AWS services, Python, and deep learning frameworks like Keras. The project integrated cloud-based solutions using CloudFormation, Lambda, and Gateway for scalable and efficient deployment, using SQL and DynamoDB for data management.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"14\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Assistance for Seniors<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For the Austrian Institute of Technology (as a part of the national research project LARAH), a prototype of an assistance system for visual indoor localization for disabled and elderly persons was developed. By leveraging Computer Vision and Deep Learning, innovative algorithms for position determination were implemented. The project resulted in a functional prototype, including two Android applications for real-time localization. Key elements included:<br \/>\n- visual recognition of persons using Deep-Learning models<br \/>\n- visual reconstruction and localization of indoor environments using Structure-from-Motion and Machine Learning algorithms<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"366\" height=\"451\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png 366w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-10x12.png 10w\" sizes=\"(max-width: 366px) 100vw, 366px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, developed under Python using Deep Learning models like TensorFlow, custom-developed Structure-from-Motion software and custom camera calibration software. Additionally, as a part of the project, two Android apps were modified and integrated together onto the Robot Operating System on the mobile platform.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"1\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Electrical Switch Monitor<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a public transportation network, the objective was to optimize the monitoring of their legacy electrical switchboards. These decade-old items that are often located in very remote areas are prone to failures and tracking of errors was not possible. The objective was to enable real-time tracking and the recognition of upcoming failures from changed switching behavior. The key elements were:<\/p>\n<ul>\n<li>Development of specific hardware configuration with custom housings (3D printed) to mount instead of regular switchboard covers;<\/li>\n<li>Camera control and initial image generation on Raspberry Pi integrated in housing;<\/li>\n<li>Initial scan of switch layout and labels;<\/li>\n<li>Identification of switching operations and registration of new positions;<\/li>\n<li>Identification of irregular switching patterns (delays, other irregularities) to indicate upcoming failures for predictive maintenance;<\/li>\n<li>Update of central database and cloud solution with last state and observed switching patterns;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"959\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-1024x959.jpg\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-980x918.jpg 980w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-480x450.jpg 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1024px, 100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>The solution was implemented using Python on Raspberry Pi devices, backbone and cloud processing were done using a LAMP stack, with PyTorch, TensorFlow and OpenCV.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"5\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">Hydropower Plant Operations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><div class=\"et_pb_column_11 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_6_24 et_flex_column_12_24_tablet et_flex_column_24_24_phone et_flex_column_12_24_tabletWide preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_2 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module hovergroup preset--group--divi-blurb--divi-box-shadow--default preset--group--divi-blurb--divi-font-body--h19rs5u--7p5s44libg preset--group--divi-blurb--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_content et_flex_module\">\n<div class=\"et_pb_blurb_container\">\n<div class=\"et_pb_blurb_description\">\n<p>Create an integrated monitoring and surveillance solution for small-scale hydropower plants in remote locations. The solution included a full range of required settings:<\/p>\n<ul>\n<li>real-time monitoring and logging of operations<\/li>\n<li>failure detection and automated<\/li>\n<li>predictive maintenance logic to identify early failure<\/li>\n<li>camera-based intrusion and irregularity detection<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was a hybrid solution using Siemens PLCs, combined with small edge computing elements (Raspberry Pi and Arduino). All primary logic (particularly shutdown and load adjustment) was local, but key decisions and aggregations were executed online based on regular data transmission to a cloud-based management and operations suite.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"2\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Customer Interaction Analysis<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a project management SaaS solution where customers were matched with freelancers, a custom AI solution was established with the purpose to improve experiences for all parties. Key purposes were to create an early warning system to help customer service intervene in case of issues:<\/p>\n<ul>\n<li>Identification of unusual patterns (delays indicating inaction, intense exchanges);<\/li>\n<li>Flagging of language transgressions on both sides (use of inappropriate language, aggression);<\/li>\n<li>Matching of final ratings with evaluation of flow and dialogue quality to foster a more honest rating culture;<\/li>\n<li>Language style matching to improve future matching of freelancers to clients;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was implemented using Python on a LAMP stack, with self-developed machine learning libraries.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"6\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-shirt\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">Motion-sensitive wearables<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Arduino-based, with edge ml functionality and periodic link via BLE to connected phone. Machine learning algorithms on cloud detecting various health states and delivering alerts to phone or web app. All logic woven into a cotton fabric wristband.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"4\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-network-wired\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">IT Operations Automation<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>The objective of this project was to identify approaches on integration automation approaches and AI to more stably and reliably document and manage a highly complex IT environment with systems ranging from legacy mainframes to local server farms to cloud services. The objective was a massive simplification of maintaining up-to-date system views, status views and predictive error management.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/governance-and-ethics\">Governance<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><\/div><div class=\"nsp-overlay\" id=\"nsp-overlay\" role=\"dialog\" aria-modal=\"true\"><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>9senses helps organizations turn artificial intelligence into real business value through strategy, governance, data management, and practical AI transformation.<\/p>","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-646","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/646","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/comments?post=646"}],"version-history":[{"count":75,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/646\/revisions"}],"predecessor-version":[{"id":228564,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/646\/revisions\/228564"}],"wp:attachment":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/media?parent=646"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}