AI agents are changing how enterprises operate. To make them better, you need to understand how they behave. We build the platforms, methods, and expertise to make that possible.
We study how agents plan, use tools, recover from failure, and interact with humans. Evaluation and measurement make that understanding precise.
Infrastructure for understanding agent behavior.
Capture full behavioral traces in isolated, enterprise-grade environments. Run controlled experiments at scale to find patterns that manual evaluation misses. Analyze decision sequences, tool use, and failure modes — then benchmark across agents, prompts, and configurations.
Advancing the science of agent behavior.
We develop new methods to characterize agent behavior — across tool use, multi-step planning, error recovery, and human coordination. Our work includes behavioral taxonomies, failure mode analysis, and measurement frameworks that go beyond pass/fail.
Rigorous measurement of agent behavior.
We design evaluation frameworks — tasks, rubrics, datasets, and scoring methods — tailored to how your agent operates. Automated measurement at scale with reproducible results. A/B and variant analyses to quantify the impact of every change.
Making agent behavior legible to the teams that build them.
We work alongside your team to turn behavioral observations and evaluation results into clear recommendations. We characterize failure modes, identify paths to improvement, and deliver evidence-backed guidance.
You build agents. We help you understand what they actually do.
→ The Context Lab Platform