BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Graphwise - ECPv6.17.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-ORIGINAL-URL:https://gws-sso-test.graphwise.ai X-WR-CALDESC:Events for Graphwise REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Europe/Vienna BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20251026T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20260329T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20261025T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20270328T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20271031T010000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=Europe/Vienna:20260211T160000 DTEND;TZID=Europe/Vienna:20260211T170000 DTSTAMP:20260225T090928Z CREATED:20251219T124458Z LAST-MODIFIED:20260225T090928Z UID:244346-1770825600-1770829200@gws-sso-test.graphwise.ai SUMMARY:From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact DESCRIPTION:On-Demand WEBINAR \n \n \n \n \n \n From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact\n \n \n \n \n \n \n \n \n \n February 11\, 2026 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Susan Härtig \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n Fill out the form to watch this webinar\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Many enterprises are excited about generative AI\, but turning that excitement into scalable results often proves difficult. The challenge is that most enterprise data is complex\, interconnected\, and highly contextual. Traditional large language models can generate fluent text\, but they don’t truly understand the domain. \nWatch a webinar hosted together with our partners at Tietoevry\, where we’ll explore how Knowledge Graph-driven Retrieval-Augmented Generation (RAG) helps AI move from guessing to genuine understanding. \nMohammad Shadab\, Senior Data Architect\, and Sebastian Remnerud\, Senior Solution Consultant at Tietoevry\, will walk through two real customer cases that show how this approach works in practice: \nCase 1: Turning IoT data into meaningful insightsSensor data alone rarely tells the full story. By combining knowledge graphs\, LLMs and enriching IoT data with external sources such as weather\, organizations connect previously unrelated signals and move beyond basic monitoring to enable predictive maintenance and profitability insights.The result: IoT data that finally tells a clear story\, enabling predictive actions and confident decisions. \nCase 2: Smarter recipes with domain-aware AIBy grounding generative AI in structured domain knowledge\, this solution significantly improves content quality\, dietary constraint detection\, and personalized recipe recommendations\, enabling intelligent recipe transformation while preserving nutritional intent and culinary context.The result: Now users can trust AI because it understands the domain\, not just the words on the page. \nWhether you’re working with enterprise data\, AI initiatives\, or IoT systems\, this session will offer practical insights you can apply right away! Along with time to raise your own questions and challenges. \n​ \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the webinar\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n Speaker\n \n \n \n \n \n \n \n \n \n \n \n \n Susan Härtig URL:https://gws-sso-test.graphwise.ai/event/from-culinary-to-iot-how-tietoevry-delivers-real-semantic-ai-impact/ CATEGORIES:On-demand Webinar ATTACH;FMTTYPE=image/png:https://gws-sso-test.graphwise.ai/wp-content/uploads/2025/12/How-Tietoevry-Delivers-Real-Semantic-AI-Impact-scaled.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/Vienna:20260211T160000 DTEND;TZID=Europe/Vienna:20260211T170000 DTSTAMP:20251219T124458Z CREATED:20251219T124458Z LAST-MODIFIED:20251219T124458Z UID:252313-1770825600-1770829200@gws-sso-test.graphwise.ai SUMMARY:From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact DESCRIPTION:On-Demand WEBINAR \n \n \n \n \n \n From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact\n \n \n \n \n \n \n \n \n \n February 11\, 2026 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Susan Härtig \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n Fill out the form to watch this webinar\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Many enterprises are excited about generative AI\, but turning that excitement into scalable results often proves difficult. The challenge is that most enterprise data is complex\, interconnected\, and highly contextual. Traditional large language models can generate fluent text\, but they don’t truly understand the domain. \nWatch a webinar hosted together with our partners at Tietoevry\, where we’ll explore how Knowledge Graph-driven Retrieval-Augmented Generation (RAG) helps AI move from guessing to genuine understanding. \nMohammad Shadab\, Senior Data Architect\, and Sebastian Remnerud\, Senior Solution Consultant at Tietoevry\, will walk through two real customer cases that show how this approach works in practice: \nCase 1: Turning IoT data into meaningful insightsSensor data alone rarely tells the full story. By combining knowledge graphs\, LLMs and enriching IoT data with external sources such as weather\, organizations connect previously unrelated signals and move beyond basic monitoring to enable predictive maintenance and profitability insights.The result: IoT data that finally tells a clear story\, enabling predictive actions and confident decisions. \nCase 2: Smarter recipes with domain-aware AIBy grounding generative AI in structured domain knowledge\, this solution significantly improves content quality\, dietary constraint detection\, and personalized recipe recommendations\, enabling intelligent recipe transformation while preserving nutritional intent and culinary context.The result: Now users can trust AI because it understands the domain\, not just the words on the page. \nWhether you’re working with enterprise data\, AI initiatives\, or IoT systems\, this session will offer practical insights you can apply right away! Along with time to raise your own questions and challenges. \n​ \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the webinar\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n Speaker\n \n \n \n \n \n \n \n \n \n \n \n \n Susan Härtig URL:https://gws-sso-test.graphwise.ai/event/from-culinary-to-iot-how-tietoevry-delivers-real-semantic-ai-impact-2/ CATEGORIES:On-demand Webinar ATTACH;FMTTYPE=image/png:https://gws-sso-test.graphwise.ai/wp-content/uploads/2025/12/How-Tietoevry-Delivers-Real-Semantic-AI-Impact-scaled.png END:VEVENT END:VCALENDAR