Live, March 25th, 2026, @2pm EST

AI is rapidly becoming embedded in the software development lifecycle. Yet many organizations are discovering a hard truth: intelligence without context is unreliable. Models generate plausible output, but they lack awareness of system architecture, internal policies, API contracts, ownership structures, and downstream impact. In enterprise environments, that gap is where risk lives.

Trusted AI is not simply about model quality. It is about grounding AI in the real, structured context of your organization.

In this SDTimes webinar, Tabnine explores how enterprises can move from experimental AI usage to production-grade, trustworthy systems. We will discuss how building a living model of your codebase and development ecosystem enables AI to reason about dependencies, understand blast radius, respect architectural decision records, and operate within governance boundaries.

Attendees will learn:

- Why accuracy alone is insufficient for enterprise AI adoption

- What it means to operationalize trust across architecture, compliance, and security

- How structured context modeling differs from document retrieval approaches

- How context-aware AI reduces rework, prevents downstream failures, and improves developer velocity

- Practical considerations for scaling AI across large engineering organizations

- How enterprise context can be used to enhance your existing agentic AI coding solution (Cursor, Claude Code, Github Copilot, Tabnine and more)

The next phase of enterprise AI is not bigger models. It is smarter systems that understand the environment they operate in. Join us to explore how context-driven AI enables software teams to move faster with confidence.

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