practical
The Evidence Plane for AI Systems
The missing layer between what your system must prove and how your organization proves it. A framework synthesis connecting obligations, controls, evaluations, evidence artifacts, and the response loop.
Choosing Your Eval Architecture
The question is not which eval tool. The question is what kind of eval infrastructure your system actually needs. Three architectures, three failure modes, and how they compose into an evidence pipeline.
The Regulatory Mapping Table
An interactive reference that turns EU AI Act high-risk obligations into operating controls, verification methods, evidence artifacts, owners, and review cadence. Filter by role, article, cluster, or cadence to map obligations into your operating responsibilities.
What Your Agent Logged vs. What the Auditor Needed
The trace says what happened. The auditor asks why, under what authority, and what changed. Most agent deployments log enough to debug a success but not enough to investigate a failure.
Drift Detection Patterns for Production Agents
Your agent is still answering. That does not mean it is still behaving the same way. Five drift classes, three detection layers, and the patterns that catch regression before your customers do.
From Obligation to Evidence in 90 Minutes
Pick one requirement. Map it to a control. Write the eval. Generate the artifact. Assign the owner. A hands-on walkthrough of the full compliance loop using EU AI Act Article 14.
Building an Eval Harness That Survives Production
Most eval harnesses die the same way. Five structural decisions separate the ones that survive production from the ones that quietly rot.