Give Agents Context for
Evals and Production

In this session, Chalk Co-Founder Elliot Marx will show how a unified context layer solves AI agent accuracy and evals. A context layer delivers real-time context for AI decisions by assembling data at inference time, like the sum of transfer amounts in the last 10 minutes or the number of open disputes at the moment a user interacts with your agent. The same system powers testing, evals, and production, so you can deploy agents with confidence.

We'll demonstrate how to:

• Test agents in a simulated time-bound environment with governed data and tool access
• Evaluate agents on realistic scenarios and review traces to identify failures
• Run agents in secure sandboxes and monitor for unexpected behavior
• Deliver real-time data straight from the source to your agents at the moment users interact