Real Benchmarks. Real Stakes.
Measuring AI agent performance under actual business constraints, not synthetic puzzles.
Standard AI benchmarks measure performance in isolation — perfect inputs, unlimited resources, zero stakes. That's not how business works.
Pressure Chamber runs our AI CMO under varying real-world constraints and measures actual business outcomes. Token limits, API rate caps, latency budgets, restricted tool access, noisy context — the constraints that define production AI.
We don't ask "can the AI solve this puzzle?" We ask "can the AI generate qualified leads under a 4K token budget with 50ms latency caps?"
Each axis represents a real constraint AI agents face in production environments.
Context window limits. How does output quality degrade as available tokens shrink from 128K to 4K?
Rate limiting pressure. Can the agent complete its workflow with 10 API calls instead of 100?
Latency constraints. What's achievable in 100ms vs 10 seconds? First-token latency matters.
Feature tiers. Full toolset vs restricted subset — which tools are essential, which are luxuries?
Context pollution. How much irrelevant information can be injected before performance degrades?
Metrics that tie directly to revenue and efficiency.
Efficiency ratio
Token spend efficiency
Latency impact
Output scoring
End-to-end success
Deploy your own AI CMO and see how it performs under real constraints.