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Im Gespräch wurde deutlich: Es gab vier völlig unterschiedliche Produktvisionen.",[463],{"type":320,"attrs":464},{"color":322},{"type":20,"attrs":466,"content":467},{"textAlign":22},[468],{"text":469,"type":26,"marks":470},"Durch das Konfigurieren der Skalen entstand dann jedoch ein gemeinsames Bild. Die KI sollte kein autonomer Co-Pilot werden und auch keine emotionale Figur verkörpern. Stattdessen formte sich die Vision eines situationsbewussten Service-Guides, der:",[471],{"type":320,"attrs":472},{"color":322},{"type":474,"content":475},"bullet_list",[476,487,497,507,517],{"type":477,"content":478},"list_item",[479],{"type":20,"attrs":480,"content":481},{"textAlign":22},[482],{"text":483,"type":26,"marks":484},"nur in sicheren Kontexten proaktiv wird",[485],{"type":320,"attrs":486},{"color":322},{"type":477,"content":488},[489],{"type":20,"attrs":490,"content":491},{"textAlign":22},[492],{"text":493,"type":26,"marks":494},"alle Empfehlungen mit Quellen belegt",[495],{"type":320,"attrs":496},{"color":322},{"type":477,"content":498},[499],{"type":20,"attrs":500,"content":501},{"textAlign":22},[502],{"text":503,"type":26,"marks":504},"keine Entscheidungen trifft",[505],{"type":320,"attrs":506},{"color":322},{"type":477,"content":508},[509],{"type":20,"attrs":510,"content":511},{"textAlign":22},[512],{"text":513,"type":26,"marks":514},"sachlich kommuniziert",[515],{"type":320,"attrs":516},{"color":322},{"type":477,"content":518},[519],{"type":20,"attrs":520,"content":521},{"textAlign":22},[522],{"text":523,"type":26,"marks":524},"klar innerhalb gesetzlicher Sicherheitsgrenzen operiert",[525],{"type":320,"attrs":526},{"color":322},{"type":20,"attrs":528,"content":529},{"textAlign":22},[530],{"text":531,"type":26,"marks":532},"Diese Klarheit hätte kein Briefing-Dokument der Welt erzeugt. Sie entstand durch das gemeinsame Durchlaufen der Skalen – durch das Sprechen über Grenzen, Ambitionen, Sorgen und Erwartungen.",[533],{"type":320,"attrs":534},{"color":322},{"_uid":536,"media":537,"video":41,"headline":41,"component":359,"aspectRatio":360,"preserveAspectRatio":45},"1dede0c4-3542-4ebe-b794-e635e0829c86",{"id":538,"alt":539,"name":540,"focus":41,"title":540,"source":41,"filename":541,"copyright":542,"fieldtype":43,"meta_data":543,"is_external_url":45},133892174335128,"Five people in a brightly lit office sitting around a table with laptops, engaged in a discussion and smiling. Whiteboard in the background.","Orientierung finden mit dem KI-Kompass","https://a.storyblok.com/f/180740/5472x3648/dff6338d80/ki-kompass_workshop.jpg","Ergosign",{"alt":539,"title":540,"source":41,"copyright":542},{"_uid":545,"intro":546,"content":570,"component":409},"cb866ed3-05e8-49dd-948b-46b4c72786e0",[547],{"cta":548,"_uid":549,"text":550,"headline":554,"component":304},[],"f022aaa8-d4ff-46a0-b1ed-2a4232353be4",{"type":17,"content":551},[552],{"type":20,"attrs":553},{"textAlign":22},{"type":17,"content":555},[556],{"type":293,"attrs":557,"content":558},{"level":295,"textAlign":22},[559,564],{"text":560,"type":26,"marks":561},"Warum der ",[562],{"type":320,"attrs":563},{"color":322},{"text":565,"type":26,"marks":566},"KI-Kompass wirkt",[567,569],{"type":320,"attrs":568},{"color":322},{"type":303},[571],{"id":41,"_uid":572,"content":573,"component":408},"936bc455-4744-4b01-9172-8d177a712380",[574],{"_uid":575,"text":576,"headline":41,"component":351},"3341b5bb-2b7c-4a81-bec2-2350c594ea6f",{"type":17,"content":577},[578,586,605],{"type":20,"attrs":579,"content":580},{"textAlign":22},[581],{"text":582,"type":26,"marks":583},"Unsere Erfahrung – und auch zahlreiche Veröffentlichungen von Google, IBM, Microsoft und unabhängigen Research-Gruppen – zeigen immer wieder: KI-Projekte scheitern selten an der Technologie. Sie scheitern an etwas viel Menschlicherem: unklaren Anforderungen, fehlender gemeinsamer Sprache und unterschiedlichen Erwartungshaltungen zwischen Business, Design, Legal und Tech. Oft beginnen Teams hochmotiviert, nur um Wochen später festzustellen, dass alle von etwas anderem sprechen.",[584],{"type":320,"attrs":585},{"color":322},{"type":20,"attrs":587,"content":588},{"textAlign":22},[589,594,600],{"text":590,"type":26,"marks":591},"Nach mehreren Iterationen und im Austausch mit Experten aus unterschiedlichen Fachbereichen wie IT Engineering, Data Science, Entwicklern und Projektmanagement sowie UX-Designern geht unser KI-Kompass genau dieses Problem an. Er übersetzt abstrakte KI-Konzepte in konkrete Entscheidungen und bringt so alle Stakeholder auf eine gemeinsame Linie. Er legt Leitplanken fest, bevor Ressourcen investiert werden, und verhindert teure Umwege oder Fehlentwicklungen. Noch bevor der erste Workshop beginnt, entsteht ein gemeinsames KI-Profil – ein klares Bild davon, wie das System funktionieren und wirken soll und welche Richtung es bewusst ",[592],{"type":320,"attrs":593},{"color":322},{"text":595,"type":26,"marks":596},"nicht",[597,599],{"type":320,"attrs":598},{"color":322},{"type":345},{"text":601,"type":26,"marks":602}," einschlagen darf.",[603],{"type":320,"attrs":604},{"color":322},{"type":20,"attrs":606,"content":607},{"textAlign":22},[608],{"text":609,"type":26,"marks":610},"Was bleibt, ist kein nebulöser Wunsch nach „irgendeinem KI-Mehrwert“, sondern strategische Orientierung: ein Projekt, das bewusst, fokussiert und mit einer geteilten Vision startet.",[611],{"type":320,"attrs":612},{"color":322},{"_uid":614,"intro":615,"content":644,"component":409},"8304c489-64a1-4f98-8c47-008eb4a2a4ca",[616],{"cta":617,"_uid":618,"text":619,"headline":623,"component":304},[],"676ae329-05ed-4c93-b0fc-e3cdf550d346",{"type":17,"content":620},[621],{"type":20,"attrs":622},{"textAlign":22},{"type":17,"content":624},[625],{"type":293,"attrs":626,"content":627},{"level":295,"textAlign":22},[628,633,639],{"text":629,"type":26,"marks":630},"Was am ",[631],{"type":320,"attrs":632},{"color":322},{"text":634,"type":26,"marks":635},"Ende",[636,638],{"type":320,"attrs":637},{"color":322},{"type":303},{"text":640,"type":26,"marks":641}," steht",[642],{"type":320,"attrs":643},{"color":322},[645],{"id":41,"_uid":646,"content":647,"component":408},"45026525-0bbd-490d-8a7d-7588b27f5ab6",[648],{"_uid":649,"text":650,"headline":41,"component":351},"e32ebfa2-6eb3-4ed4-8ff3-94691c3ebabf",{"type":17,"content":651},[652,660,668],{"type":20,"attrs":653,"content":654},{"textAlign":22},[655],{"text":656,"type":26,"marks":657},"Der KI-Kompass liefert kein fertiges Konzept. Aber er liefert etwas, das in dieser frühen Phase weit wertvoller ist: ein klar beschriebenes KI-Systemprofil. Ein gemeinsames Bild davon, welche Rolle die KI übernehmen soll, wie viel Einfluss sie auf die Nutzer hat, wie transparent sie sein muss und welche Grenzen sie nicht überschreiten darf.",[658],{"type":320,"attrs":659},{"color":322},{"type":20,"attrs":661,"content":662},{"textAlign":22},[663],{"text":664,"type":26,"marks":665},"Dieses Profil ist strategisch formuliert und für alle verständlich. Es bildet den idealen Startpunkt für jeden AI-Ideation-Workshop – und die Grundlage für ein verantwortungsvolles, nutzerzentriertes und markenkonformes KI-Produkt.",[666],{"type":320,"attrs":667},{"color":322},{"type":20,"attrs":669,"content":670},{"textAlign":22},[671],{"text":672,"type":26,"marks":673},"Der größte Fehler in KI-Projekten ist, zu früh mit der Umsetzung zu beginnen. Der zweitgrößte: ohne gemeinsame Sprache zu starten. Wenn Sie Ihr KI-Projekt nicht dem Zufall überlassen möchten und mit Orientierung statt Bauchgefühl starten wollen: Lassen Sie uns gemeinsam Ihren KI-Kompass ausrichten.",[674],{"type":320,"attrs":675},{"color":322},[677],{"_uid":678,"media":679,"headline":685,"component":694},"e62c3a6c-86b2-4538-8faf-c5de4c1f88d5",{"id":680,"alt":681,"name":41,"focus":41,"title":682,"source":41,"filename":683,"copyright":41,"fieldtype":43,"meta_data":684,"is_external_url":45},133884419971977,"A futuristic, glowing compass with a transparent dome displays a blue and pink needle, set on a dark background.","Der KI-Kompass","https://a.storyblok.com/f/180740/3840x2160/3de7b60086/ki_kompass_header.png",{"alt":681,"title":682,"source":41,"copyright":41},{"type":17,"content":686},[687],{"type":293,"attrs":688,"content":690},{"level":689,"textAlign":22},1,[691],{"text":276,"type":26,"marks":692},[693],{"type":303},"MediaHero",[696],"cfa8e739-dc5b-4239-ab1b-97232ab94ef1",[698],"6c327e6a-b387-4056-a36c-d5f33b79bed3",[700,701],"2b5052bc-db30-4ae9-87f0-ede87bb56855","c68efb2e-60c7-4bd6-a9ed-a1a52ba0a965",[703],{"id":41,"_uid":704,"form":705,"intro":706,"target":727,"contact":728,"component":729,"textFailure":730,"textSuccess":733,"titleFailure":736,"titleSuccess":739,"shouldRedirect":45,"buttonSuccessLabel":41,"googleAnalyticsEvent":41,"trackGoogleAnalytics":45},"48350e14-d162-4dc4-a863-7cebb2c5f825","30bb3154-6b97-41ea-aa21-55a700818918|||3780485|||2602_Kontaktformular_Development_DE",[707],{"cta":708,"_uid":709,"text":710,"headline":717,"component":304},[],"d7e54876-c278-40fa-9a87-70c8b676484d",{"type":17,"content":711},[712],{"type":20,"attrs":713,"content":714},{"textAlign":22},[715],{"text":716,"type":26},"Wir zeigen Ihnen, wie Sie KI-Projekte mit klarem Fahrplan und UX-Exzellenz erfolgreich umsetzen. 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",[755],{"type":320,"attrs":756},{"color":322},{"text":758,"type":26,"marks":759},"Doch eine zentrale Frage bleibt offen:",[760,762],{"type":320,"attrs":761},{"color":322},{"type":303},{"text":764,"type":26,"marks":765}," Was genau soll diese KI eigentlich tun? ",[766],{"type":320,"attrs":767},{"color":322},{"type":20,"attrs":769,"content":770},{"textAlign":22},[771],{"text":772,"type":26,"marks":773},"Sobald die ersten konkreten Gespräche stattfinden, tauchen Unsicherheiten auf, denn oft fehlt eine “gemeinsame Sprache\", um Ambitionen verständlich auszudrücken. Teams sprechen über KI, aber jeder meint etwas anderes. So entsteht in dieser frühen Phase ein diffuses Gefühl der Orientierungslosigkeit – nicht unbedingt wegen fehlenden Wissens, sondern aufgrund fehlender gemeinsamer Begriffe. ",[774],{"type":320,"attrs":775},{"color":322},{"type":20,"attrs":777,"content":778},{"textAlign":22},[779,784,793],{"text":780,"type":26,"marks":781},"Und wenn ein Projekt unter diesen Vorzeichen startet, läuft es oft in Schlangenlinien: widersprüchliche Erwartungen, zu viele Richtungswechsel, teure Iterationen und ein wachsendes Risiko, dass die Lösung am Ende weder nutzerzentriert noch markenkonform ist. Das bestätigt der Bericht des Massachusetts Institute of Technology (MIT): 95% aller KI-Projekte scheitern bei der Umsetzung und erzielen keine Erträge. 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Das Ergebnis ist eine effiziente, nutzerfreundliche Anwendung mit erweiterten Funktionen, einem modernen Design und einer zukunftssicheren technologischen Basis für kontinuierliche Weiterentwicklung.","Die Ausgangslage",{"_uid":1014,"media":1015,"video":41,"autoplay":45,"headline":41,"component":359,"showBorder":45,"aspectRatio":360,"preserveAspectRatio":45},"b5114f7e-b544-49fa-85fc-cb5f4f8f3037",{"id":1016,"alt":1017,"name":41,"focus":41,"title":1018,"source":542,"filename":1019,"copyright":542,"fieldtype":43,"meta_data":1020,"is_external_url":45},16911522,"Eine Kamera von Vision Research zur linken Seite und zur rechten Seite ein Ausschnitt aus dem UI","Vision Research Redesign","https://a.storyblok.com/f/180740/1920x1080/d145f2d4dd/cs_vision-research_slide1_v1.jpg",{"alt":1017,"size":1021,"title":1018,"source":542,"copyright":542},"1920x1080",{"_uid":1023,"intro":1024,"content":1043,"component":409},"4bf6f3ad-3fa6-486c-93fa-262e410eece3",[1025],{"cta":1026,"_uid":1027,"text":1028,"headline":1032,"component":304},[],"93254bda-dc83-4aea-b089-528cceeaf612",{"type":17,"content":1029},[1030],{"type":20,"attrs":1031},{"textAlign":22},{"type":17,"content":1033},[1034],{"type":20,"attrs":1035,"content":1036},{"textAlign":22},[1037,1039],{"text":1038,"type":26},"Von Strategie und Design bis hin zur ",{"text":1040,"type":26,"marks":1041},"maßgeschneiderten Entwicklung",[1042],{"type":303},[1044],{"id":41,"_uid":1045,"content":1046,"component":408},"8cd468db-719d-4f7b-b8f8-9c05c1f65482",[1047,1062,1070],{"_uid":1048,"text":1049,"headline":1061,"component":351},"5b22630a-237f-4a2a-bc72-23401d4f14f7",{"type":17,"content":1050},[1051,1056],{"type":20,"attrs":1052,"content":1053},{"textAlign":22},[1054],{"text":1055,"type":26},"Unser Ansatz umfasste drei zentrale Phasen. In der Strategiephase stimmten wir die Ziele von AMETEK/Vision Research mit den Anforderungen der Nutzenden sowie den technischen Anforderungen ab. Auf Basis von globalen Kontextanalysen und den so gewonnenen Insights wurden notwendige Verbesserungen und neue Funktionen identifiziert. Diese halfen uns dabei, die Nutzererfahrung zu optimieren. Zudem definierten wir die Grundlagen für Datenverbindungen und die App-Architektur, um Umsetzungsstrategien und Frontend-Technologien zu evaluieren.",{"type":20,"attrs":1057,"content":1058},{"textAlign":22},[1059],{"text":1060,"type":26},"In der anschließenden UX Design-Phase entwickelten wir aus ersten Konzepten einen High Fidelity- Prototypen, der die zuvor identifizierten Anforderungen aufgriff. Mit Hilfe des Prototyps wurden die erarbeiteten Konzepte in Usability Tests validiert und auf Basis des Feedbacks vor der finalen Entwicklung weiter verfeinert. Darüber hinaus entstand ein neues visuelles Design. Es verbindet moderne Trends mit der Corporate Identity von AMETEK/Vision Research und wird durch ein neues Icon-Set sowie eine Auswahlmöglichkeit zwischen Light und Dark Theme komplettiert.","Unser Vorgehen",{"_uid":1063,"media":1064,"video":41,"autoplay":45,"headline":41,"component":359,"showBorder":45,"aspectRatio":360,"preserveAspectRatio":45},"939d6882-8531-4563-a6f6-eb1ff311966f",{"id":1065,"alt":1066,"name":41,"focus":41,"title":1067,"source":542,"filename":1068,"copyright":542,"fieldtype":43,"meta_data":1069,"is_external_url":45},16911521,"Vision Research Design System mit Fokus auf den Icons und einem Vergleich des Light & Dark Modes","Vision Research Design System","https://a.storyblok.com/f/180740/1920x1080/af06724c68/cs_vision-research_slide2_v1.jpg",{"alt":1066,"size":1021,"title":1067,"source":542,"copyright":542},{"_uid":1071,"text":1072,"headline":41,"component":351},"3db76fc6-9d3b-4d23-b7f7-d8fa538a2d27",{"type":17,"content":1073},[1074,1079,1084],{"type":20,"attrs":1075,"content":1076},{"textAlign":22},[1077],{"text":1078,"type":26},"Zunächst fokussierten wir uns auf umfassende Software Development Kit (SDK)- und Code Reviews. Wir integrierten das bestehende SDK in eine moderne C++-Umgebung und analysierten den Technologie-Stack, um die Effizienz und Wartbarkeit zu optimieren.",{"type":20,"attrs":1080,"content":1081},{"textAlign":22},[1082],{"text":1083,"type":26},"Während der Entwicklungsphase boten wir maßgeschneiderte Lösungen für eine nahtlose Integration sowie zuverlässige Kamerasteuerung. Mithilfe eines Wrapper-basierten Ansatzes beim API-Redesign wurde ein C++-Layer für plattformübergreifende Funktionalität aufgebaut. Unser agiler Ansatz - „Release early and often“ - ermöglichte mit Hilfe einer CI/CD-Automatisierungspipeline ein nahtloses Building, Packaging und Testing. So konnte AMETEK/Vision Research jederzeit flexibel auf sich ändernde Anforderungen reagieren.",{"type":20,"attrs":1085,"content":1086},{"textAlign":22},[1087],{"text":1088,"type":26},"Mit einem starken Fokus auf kontinuierliche Verbesserung und Best Practices unterstützten wir das Projekt durch unsere architektonische Expertise. Die Zusammenarbeit ermöglichte es AMETEK/Vision Research, bemerkenswerte Erfolge in der Qt-Entwicklung zu erzielen.",{"id":41,"_uid":1090,"size":1091,"asset":1092,"intro":1094,"video":1095,"autoplay":45,"component":1139,"showBorder":45,"coloredBackground":45},"4af73c3a-f772-4e93-bbfa-1a3984b94cdc","content",{"id":22,"alt":22,"name":41,"focus":22,"title":22,"source":22,"filename":41,"copyright":22,"fieldtype":43,"meta_data":1093},{},[],{"encodings":1096,"videoAsset":1134},{"av1-768":1097,"vp9-768":1102,"av1-1280":1106,"av1-1920":1110,"h264-768":1114,"vp9-1280":1118,"vp9-1920":1122,"h264-1280":1126,"h264-1920":1130},{"url":1098,"size":1099,"status":1100,"lastModified":1101},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/768-av1.webm",3041477,"encoded","2026-05-06T09:02:06.000Z",{"url":1103,"size":1104,"status":1100,"lastModified":1105},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/768-vp9.webm",4348523,"2026-05-06T08:57:36.000Z",{"url":1107,"size":1108,"status":1100,"lastModified":1109},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1280-av1.webm",4240485,"2026-05-06T09:29:20.000Z",{"url":1111,"size":1112,"status":1113,"lastModified":41},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1920-av1.webm",0,"encoding",{"url":1115,"size":1116,"status":1100,"lastModified":1117},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/768-h264.mp4",5862126,"2026-05-06T08:53:05.000Z",{"url":1119,"size":1120,"status":1100,"lastModified":1121},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1280-vp9.webm",6762718,"2026-05-06T08:59:48.000Z",{"url":1123,"size":1124,"status":1100,"lastModified":1125},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1920-vp9.webm",10328209,"2026-05-06T09:00:19.000Z",{"url":1127,"size":1128,"status":1100,"lastModified":1129},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1280-h264.mp4",10233910,"2026-05-06T08:53:25.000Z",{"url":1131,"size":1132,"status":1100,"lastModified":1133},"https://cdn.es-video-encoding.aws.ergosign-projects.com/vision_research_produktvideo/1920-h264.mp4",19900574,"2026-05-06T08:53:53.000Z",{"asset":1135,"filename":1137},{"id":1136,"alt":41,"name":41,"focus":41,"title":41,"source":41,"filename":1137,"copyright":41,"fieldtype":43,"meta_data":1138,"is_private":45},173539043021110,"https://a.storyblok.com/f/180740/x/0b50f0957b/vision_research_produktvideo.mp4",{},"MediaBlockSection",{"_uid":1141,"intro":1142,"content":1161,"component":409},"d8d98c93-3d23-4bd0-aa25-78f9cc09d295",[1143],{"cta":1144,"_uid":1145,"text":1146,"headline":1150,"component":304},[],"101d2382-5957-4f55-aa71-e70f648f4152",{"type":17,"content":1147},[1148],{"type":20,"attrs":1149},{"textAlign":22},{"type":17,"content":1151},[1152],{"type":20,"attrs":1153,"content":1154},{"textAlign":22},[1155,1157],{"text":1156,"type":26},"Modernes und ",{"text":1158,"type":26,"marks":1159},"mesch-zentriertes Design",[1160],{"type":303},[1162],{"id":41,"_uid":1163,"content":1164,"component":408},"d4ffc54e-4606-4b99-901f-7bcdae8ca7d0",[1165,1175],{"_uid":1166,"text":1167,"headline":1174,"component":351},"56f1bfed-981d-48a1-bc9b-d4ea505e97a1",{"type":17,"content":1168},[1169],{"type":20,"attrs":1170,"content":1171},{"textAlign":22},[1172],{"text":1173,"type":26},"Das Projekt resultierte in einer PCC-Anwendung der nächsten Generation, die den Anforderungen von AMETEK/Vision Research vollends gerecht wurde. Durch die frühzeitige Einbindung der Nutzenden und kontinuierliche Optimierungen entstand eine effiziente Anwendung mit modernem Design und einem anpassbaren Icon-Set. Darüber hinaus bietet die Lösung eine zukunftssichere Basis für eine nahtlose Integration plattformübergreifender Funktionalitäten und eine zuverlässige Leistung.","Unsere Lösung",{"_uid":1176,"media":1177,"video":41,"autoplay":45,"headline":41,"component":359,"showBorder":45,"aspectRatio":360,"preserveAspectRatio":45},"116f1aed-b4d0-4144-b4c4-cabee677d2a2",{"id":1178,"alt":1179,"name":41,"focus":41,"title":1067,"source":542,"filename":1180,"copyright":542,"fieldtype":43,"meta_data":1181,"is_external_url":45},16911523,"Vision Research Design System mit Fokus auf den Icons","https://a.storyblok.com/f/180740/1920x1080/678dccc0b5/cs_vision-research_slide3_v1.jpg",{"alt":1179,"size":1021,"title":1067,"source":542,"copyright":542},{"_uid":1183,"intro":1184,"content":1199,"component":409},"d7178aea-5777-4d1c-b0a9-1dc94cdd2e26",[1185],{"cta":1186,"_uid":1187,"text":1188,"headline":1192,"component":304},[],"8c83926e-1a2b-40dc-97bd-d4f90587c653",{"type":17,"content":1189},[1190],{"type":20,"attrs":1191},{"textAlign":22},{"type":17,"content":1193},[1194],{"type":20,"attrs":1195,"content":1196},{"textAlign":22},[1197],{"text":1198,"type":26},"AMETEK/Vision Research",[1200],{"id":41,"_uid":1201,"content":1202,"component":408},"d9dafe96-7f6a-45cb-9bf1-b4bfc48609e7",[1203,1213],{"_uid":1204,"text":1205,"headline":1212,"component":351},"49b295e3-31d7-4dd3-8f69-0a9f1c66200a",{"type":17,"content":1206},[1207],{"type":20,"attrs":1208,"content":1209},{"textAlign":22},[1210],{"text":1211,"type":26},"Vision Research, ein Geschäftsbereich von AMETEK Inc, ist mit seinen Phantom High-Speed- Kameras ein Marktführer im Bereich der Hochgeschwindigkeitsbildgebung. Getreu dem Motto „When it’s too fast to see, and too important not to®“ bieten Phantom-Kameras die ideale Kombination aus Auflösung, Geschwindigkeit und Empfindlichkeit für Bewegungsanalyse-Anwendungen in den Bereichen Verteidigung, Wissenschaft, Industrie und Unterhaltung.","Über den Kunden",{"_uid":1214,"media":1215,"video":41,"autoplay":45,"headline":41,"component":359,"showBorder":45,"aspectRatio":360,"preserveAspectRatio":45},"f38d87bb-1c6a-40bc-acbb-1ee6595ad3c6",{"id":1216,"alt":1217,"name":41,"focus":41,"title":1067,"source":542,"filename":1218,"copyright":542,"fieldtype":43,"meta_data":1219,"is_external_url":45},16911517,"Vision Research Design System mit Ausschnitten aus den Software Controls","https://a.storyblok.com/f/180740/1920x1080/f60ad2c108/cs_vision-research_slide4_v1.jpg",{"alt":1217,"size":1021,"title":1067,"source":542,"copyright":542},{"_uid":1221,"text":1222,"author":1246,"button":1247,"component":1248,"authorInfo":1249,"authorImage":1250,"authorLocation":961},"7433ce60-36fe-450b-a3a7-cc5470f0d0cb",{"type":17,"content":1223},[1224,1235],{"type":20,"attrs":1225,"content":1226},{"textAlign":22},[1227,1229,1233],{"text":1228,"type":26},"Ergosign startete mit Workshops, in denen wir Designentscheidungen über die Benutzeroberfläche auf Grundlage von Präferenzen der einzelnen Interessengruppen trafen. Es war großartig zu sehen, wie die Ergebnisse dieser Zusammenarbeit ",{"text":1230,"type":26,"marks":1231},"in der Prototyp-Phase zum Leben erweckt ",[1232],{"type":303},{"text":1234,"type":26},"wurden.",{"type":20,"attrs":1236,"content":1237},{"textAlign":22},[1238,1240,1244],{"text":1239,"type":26},"Jetzt, wo wir uns auf die Veröffentlichung des neuen PCC vorbereiten, können wir mit Sicherheit sagen, dass Ergosign der richtige Partner für uns bei diesem Projekt war. Wir haben nicht nur eine ",{"text":1241,"type":26,"marks":1242},"moderne neue Steuerungssoftware",[1243],{"type":303},{"text":1245,"type":26},", sondern wir haben auch viel über heutige Best Practices für die Softwareentwicklung gelernt, was mit der Benutzererfahrung beginnt und endet.","Toni Lucatorto",[],"Quote","Senior Product Manager",{"id":22,"alt":22,"name":41,"focus":22,"title":22,"source":22,"filename":41,"copyright":22,"fieldtype":43,"meta_data":1251},{},[1253],{"_uid":1254,"media":1255,"headline":1261,"component":694},"6ff725f2-a558-4c57-8823-a23ac1216676",{"id":1256,"alt":1257,"name":41,"focus":41,"title":1258,"source":542,"filename":1259,"copyright":542,"fieldtype":43,"meta_data":1260,"is_external_url":45},17881159,"A man sitting at a desk with 2 screens in front of him, on which the Vision Research application can be seen. 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Neben einem Chatbot, der bei der Benutzung der Software unterstützt, kamen als weitere Ideen KI-generierte Playlisten für Erklärvideos und ein Chatbot für Datenbankabfragen in natürlicher Sprache auf, der hilft, ohne SQL-Kenntnisse Informationen aus der Datenbank zu ziehen (SQL=Structured Query Language“ auf Deutsch: „Strukturierte Abfragesprache\"). In dieser Case Study schauen wir uns den Chatbot als konkretes Beispiel für unsere Methodik und Umsetzung an. ",{"id":41,"_uid":4234,"size":1091,"asset":4235,"intro":4240,"video":41,"component":1139,"coloredBackground":45},"848fb184-bb8a-4a14-89a0-63b26dc4b8ea",{"id":4236,"alt":4237,"name":41,"focus":41,"title":41,"source":41,"filename":4238,"copyright":542,"fieldtype":43,"meta_data":4239,"is_external_url":45},20738080,"Martin Hetzel und Sophia Antonin auf der Bühne in Nahaufnahme","https://a.storyblok.com/f/180740/1920x1080/84fd30dcca/martin-hetzel-und-sophia-antonin-auf-der-buhne.jpg",{"alt":4237,"title":41,"source":41,"copyright":542},[],{"_uid":4242,"intro":4243,"content":4261,"component":409},"81869b47-1e06-4e88-86e5-6646c615c55e",[4244],{"cta":4245,"_uid":4246,"text":4247,"headline":4250,"component":304},[],"66277b2b-d069-4ddc-9066-51c9b77132fd",{"type":17,"content":4248},[4249],{"type":20},{"type":17,"content":4251},[4252],{"type":20,"attrs":4253,"content":4254},{"textAlign":22},[4255,4257],{"text":4256,"type":26},"Machbarkeit und Qualität prüfen im ",{"text":4258,"type":26,"marks":4259},"AI Exploration Sprint",[4260],{"type":303},[4262,4285],{"id":41,"_uid":4263,"content":4264,"component":408},"fed2c959-c220-410d-8217-256b214993fd",[4265],{"_uid":4266,"text":4267,"headline":41,"component":351},"7fe302fd-ee18-4626-b63b-b9ce7536ce77",{"type":17,"content":4268},[4269],{"type":20,"attrs":4270,"content":4271},{"textAlign":22},[4272,4274,4279,4283],{"text":4273,"type":26},"SIVAS.ERP umfasst über 2500 Tabellen, 900 Programme und wird täglich von über 5000 Usern verwendet. Diese Komplexität macht deutlich: ein Chatbot, der sämtliche Funktionen der Software kennt und Fragen dazu beantworten kann, hätte das Potenzial, den Arbeitsalltag erheblich zu erleichtern. Ob die vorhandenen Daten jedoch geeignet sind, um einen solchen Chatbot zu realisieren, lässt sich nicht auf den ersten Blick beurteilen. Deshalb folgte nach dem Ideation Workshop der ",{"text":4258,"type":26,"marks":4275},[4276,4278],{"type":31,"attrs":4277},{"href":4200,"uuid":4201,"anchor":22,"target":35,"linktype":36},{"type":303},{"text":4280,"type":26,"marks":4281},",",[4282],{"type":303},{"text":4284,"type":26}," in dem wir die Idee gleich getestet und in einem Proof-of-Concept umgesetzt haben. Ein solches Proof-of-Concept ermöglicht eine realistische Bewertung der Idee anhand echter Daten. So lassen sich der Aufwand, die zu erwartende Qualität und sinnvolle nächste Schritte fundiert einschätzen.",{"id":41,"_uid":4286,"size":1091,"asset":4287,"intro":4292,"video":41,"component":1139,"coloredBackground":45},"628bde5e-b34f-4900-9aa7-78bb40700633",{"id":4288,"alt":4289,"name":41,"focus":41,"title":41,"source":41,"filename":4290,"copyright":542,"fieldtype":43,"meta_data":4291,"is_external_url":45},20720416,"AI Roadmap: von Ideation zu Exploration Sprint zu Entwicklung und Deployment","https://a.storyblok.com/f/180740/1532x874/063761afcb/ai_roadmap.png",{"alt":4289,"size":1021,"title":41,"source":41,"copyright":542},[],{"_uid":4294,"intro":4295,"content":4309,"component":409},"42b8be97-17ce-494d-912f-03f6d6ec5fbd",[4296],{"cta":4297,"_uid":4298,"text":4299,"headline":4302,"component":304},[],"eb10bdb3-8002-462e-83f6-20cb7165ccf3",{"type":17,"content":4300},[4301],{"type":20},{"type":17,"content":4303},[4304],{"type":20,"attrs":4305,"content":4306},{"textAlign":22},[4307],{"text":4308,"type":26},"Methoden",[4310],{"id":41,"_uid":4311,"content":4312,"component":408},"8854d730-b9c2-4327-a3c0-0ae1ebeb4562",[4313],{"_uid":4314,"text":4315,"headline":4347,"component":351},"908802cb-c5be-42db-85d6-4a4d8b761b26",{"type":17,"content":4316},[4317,4322,4324],{"type":20,"attrs":4318,"content":4319},{"textAlign":22},[4320],{"text":4321,"type":26},"Es gibt verschiedene Methoden, ein Sprachmodell mit firmeninternem Wissen zu füttern. Für welche Methode man sich entscheidet, hängt vom Anwendungsfall, den Kosten und der benötigten Anpassungsfähigkeit ab: ",{"type":20,"attrs":4323},{"textAlign":22},{"type":474,"content":4325},[4326,4333,4340],{"type":477,"content":4327},[4328],{"type":20,"attrs":4329,"content":4330},{"textAlign":22},[4331],{"text":4332,"type":26},"Beim In-Context Learning werden dem Modell direkt in der Eingabe (Prompt) Informationen mitgegeben, die dem Modell beim Beantworten der Frage oder Lösen der Aufgabe helfen. Das Modell wird dabei nicht verändert und man kann schnell verschiedene Dinge ausprobieren. Allerdings ist die Länge der Eingabe begrenzt.",{"type":477,"content":4334},[4335],{"type":20,"attrs":4336,"content":4337},{"textAlign":22},[4338],{"text":4339,"type":26},"Fine-Tuning verändert die Modellparameter durch zusätzliches Training auf spezifischen Daten, was dauerhafte Anpassungen ermöglicht, aber rechenintensiv und teuer ist. Zudem können die Inhalte der Daten später nicht mehr geändert werden.",{"type":477,"content":4341},[4342],{"type":20,"attrs":4343,"content":4344},{"textAlign":22},[4345],{"text":4346,"type":26},"Der Retrieval-Augmented-Generation-Ansatz kombiniert ein Sprachmodell mit einer Wissensdatenbank, aus der relevante Informationen abgerufen und dem Modell zur Verfügung gestellt werden. Das Modell kann (wie beim In-Context-Learning) die mitgelieferten Informationen nutzen, um die Antworten zu verbessern, ohne dass das Modell selbst verändert wird. Die Wissensdatenbank kann jederzeit aktualisiert werden, sodass immer die neuesten Informationen zur Verfügung stehen.","Exkurs",{"_uid":4349,"intro":4350,"content":4368,"component":409},"9c1bb47b-3000-4da0-bfad-54799e1addb5",[4351],{"cta":4352,"_uid":4353,"text":4354,"headline":4357,"component":304},[],"2c382ab7-c0b2-4b28-afdb-c5167ff11eb7",{"type":17,"content":4355},[4356],{"type":20},{"type":17,"content":4358},[4359],{"type":20,"attrs":4360,"content":4361},{"textAlign":22},[4362,4364],{"text":4363,"type":26},"Datenanalyse mithilfe von ",{"text":4365,"type":26,"marks":4366},"SQL Generierung",[4367],{"type":303},[4369],{"id":41,"_uid":4370,"content":4371,"component":408},"f0435de7-1c43-4511-be8e-68959c756ae6",[4372],{"_uid":4373,"text":4374,"headline":4411,"component":351},"d71935fb-8ac8-48f4-aeff-795fd12ddcc9",{"type":17,"content":4375},[4376,4381,4404,4406],{"type":20,"attrs":4377,"content":4378},{"textAlign":22},[4379],{"text":4380,"type":26},"Ein Chatbot, der firmeninterne Daten schnell und präzise abrufbar macht, wäre für Mitarbeitende aller Ebenen eine enorme Erleichterung. Er soll Fragen beantworten wie:",{"type":474,"content":4382},[4383,4390,4397],{"type":477,"content":4384},[4385],{"type":20,"attrs":4386,"content":4387},{"textAlign":22},[4388],{"text":4389,"type":26},"“In welchem Monat der letzten zwei Jahre hatten wir den höchsten Umsatz mit X? Wie hat sich das seitdem entwickelt?”",{"type":477,"content":4391},[4392],{"type":20,"attrs":4393,"content":4394},{"textAlign":22},[4395],{"text":4396,"type":26},"“Wie lange dauert die Nachbestellung von Verbrauchsmaterialien X und Y im Schnitt?”",{"type":477,"content":4398},[4399],{"type":20,"attrs":4400,"content":4401},{"textAlign":22},[4402],{"text":4403,"type":26},"“Wie viele Überstunden haben sich bei uns angesammelt und ist das im Jahresvergleich mehr oder weniger als in den Jahren zuvor?”",{"type":20,"attrs":4405},{"textAlign":22},{"type":20,"attrs":4407,"content":4408},{"textAlign":22},[4409],{"text":4410,"type":26},"Diese Unterstützung wollten wir bieten und haben ein Proof-of-Concept für schrempp edv entwickelt. Unser System wandelt natürliche Sprache in SQL-Abfragen um, extrahiert die relevanten Informationen aus der Datenbank und bereitet sie mit einem Sprachmodell in der gewünschten Form auf. So erhalten Nutzende direkt verwertbare Antworten – ob als Text, Tabelle oder Diagramm. Besonders für Teams ohne SQL-Kenntnisse bedeutet das einen erheblichen Effizienzgewinn, da wichtige Daten schneller und unkomplizierter verfügbar sind.","Die Lösung",{"_uid":4413,"intro":4414,"content":4432,"component":409},"c25a1eb0-ab95-43e5-bdf5-f7d54ed4d150",[4415],{"cta":4416,"_uid":4417,"text":4418,"headline":4421,"component":304},[],"3ba3bd60-4fb6-4102-84e8-ab1b6068ea47",{"type":17,"content":4419},[4420],{"type":20},{"type":17,"content":4422},[4423],{"type":20,"attrs":4424,"content":4425},{"textAlign":22},[4426,4428],{"text":4427,"type":26},"Ein vielversprechender ",{"text":4429,"type":26,"marks":4430},"Blick in die Zukunft",[4431],{"type":303},[4433],{"id":41,"_uid":4434,"content":4435,"component":408},"df1a6469-d052-43a5-94b4-4f73621db262",[4436],{"_uid":4437,"text":4438,"headline":41,"component":351},"be61ea75-9dc8-40d2-a080-ea110d209dbe",{"type":17,"content":4439},[4440,4445,4447],{"type":20,"attrs":4441,"content":4442},{"textAlign":22},[4443],{"text":4444,"type":26},"Innerhalb weniger Wochen haben wir im AI Exploration Sprint für schrempp edv mehrere Proof-of-Concepts mit äußerst vielversprechenden Ergebnissen entwickelt. Dabei konnten wir eindrucksvoll zeigen, dass Generative KI im ERP-Bereich echten Mehrwert bieten kann.",{"type":20,"attrs":4446},{"textAlign":22},{"type":20,"attrs":4448,"content":4449},{"textAlign":22},[4450],{"text":4451,"type":26},"Mit unserer KI-Expertise und den richtigen Ideen helfen wir Unternehmen, Strategien für den sinnvollen Einsatz von KI zu entwickeln und diese in die Praxis umzusetzen. Dafür braucht es nicht sofort einen vollständigen Projektauftrag – oft genügen erste Pilotprojekte, um wertvolle Erkenntnisse zu gewinnen.",{"_uid":4453,"intro":4454,"content":4468,"component":409},"4695682f-00c0-44e3-88b0-e3c72ab30970",[4455],{"cta":4456,"_uid":4457,"text":4458,"headline":4461,"component":304},[],"22c9c702-adf8-488d-a94d-e95d2b219ad6",{"type":17,"content":4459},[4460],{"type":20},{"type":17,"content":4462},[4463],{"type":20,"attrs":4464,"content":4465},{"textAlign":22},[4466],{"text":4467,"type":26},"schrempp edv",[4469],{"id":41,"_uid":4470,"content":4471,"component":408},"f0fe48d6-ca30-4d1a-9d0c-dd98c4d787ee",[4472],{"_uid":4473,"text":4474,"headline":1212,"component":351},"8d9b745c-1b98-4d4c-9a58-41cdb130317c",{"type":17,"content":4475},[4476,4481],{"type":20,"attrs":4477,"content":4478},{"textAlign":22},[4479],{"text":4480,"type":26},"Schrempp edv entwickelt, vertreibt und betreut seit 1980 innovative, branchenoptimierte ERP-Systeme für Maschinen- und Anlagenbauer im Mittelstand. Das Aushängeschild ist die Software SIVAS.ERP, für die wir mehrere KI-Ideen als Proof of Concept umgesetzt haben. Dieses Projekt hat unserem Kunden gezeigt, wie wichtig es ist, in Zukunft KI-Nutzung von Anfang an mitzudenken und somit die Daten entsprechend zu strukturieren — wir freuen uns bereits auf die nächsten Schritte! 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Etwas ist schief gegangen. Bitte versuchen Sie es später noch einmal oder kontaktieren Sie uns per E-Mail.",{"type":17,"content":4554},[4555],{"type":20,"attrs":4556,"content":4557},{"textAlign":22},[4558],{"text":4559,"type":26},"Wir werden Ihre Anfrage in Kürze bearbeiten und uns bei Ihnen melden.",[4561],{"cta":4562,"_uid":4563,"text":4564,"headline":4579,"component":304},[],"2968fa99-2668-4115-8f15-3a23f0617955",{"type":17,"content":4565},[4566,4574],{"type":20,"attrs":4567,"content":4568},{"textAlign":22},[4569],{"text":4570,"type":26,"marks":4571},"Lassen Sie uns gemeinsam digitale Lösungen entwickeln, die in der Praxis verlässlich überzeugen.",[4572],{"type":320,"attrs":4573},{"color":1610},{"type":20,"attrs":4575,"content":4576},{"textAlign":22},[4577],{"text":4578,"type":26},"Wir freuen uns auf den Austausch!",{"type":17,"content":4580},[4581],{"type":20,"attrs":4582,"content":4583},{"textAlign":22},[4584,4586,4590],{"text":4585,"type":26},"Bereit für den ",{"text":4587,"type":26,"marks":4588},"nächsten Schritt",[4589],{"type":303},{"text":4591,"type":26},"?",{"type":17,"content":4593},[4594],{"type":20,"attrs":4595,"content":4596},{"textAlign":22},[4597],{"text":4598,"type":26,"marks":4599},"Oops! 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