Webinars
The Context Problem: Building AI Your Organization Can Actually Trust
Venue
Zoom (link will be provided)
Available worldwide
Duration
30 minutes
Trusted AI starts with trusted context.
When agents have access to governed definitions, consistent business logic, and a semantic layer designed for how AI actually reasons, the outputs hold up. That's the shift this session is built around.
Peter Fedoročko (Field CTO, GoodData.AI) and Jan Pansky (Sr. AI Solution Architect, GoodData.AI) dig into the context problem in a 30-minute live conversation built for data leaders and practitioners who are ready to move AI beyond the pilot stage.
We’ll talk about:
- Why ungoverned data (not AI immaturity) is blocking production deployments
- How a governed context layer gives AI agents the consistent, auditable foundation they need
- What it takes to build data infrastructure that makes AI outputs reliable enough to act on
Come with your questions. Leave with a clearer path to AI you can actually trust.
Meet the speakers
Peter is Field CTO at GoodData, with deep expertise in AI, analytics, and startup leadership. He previously co-founded Understand Labs and has a background as a founder and CTO in analytics-focused technology ventures. At GoodData, he helps accelerate the company’s AI-driven vision, working closely with engineering and product teams to bring agentic and explainable analytics experiences to market.
Jan is an AI Solution Architect with a background in data science and analytics engineering. He works with organizations to design scalable, high-impact solutions that combine modern AI capabilities with strong data and analytics foundations. Drawing on deep experience in pre-sales, solution design, and customer strategy, he helps bridge business objectives and technical execution through clear communication, practical architecture, and a focus on measurable outcomes.
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