Kimpton

Founded 2025

Evaluate AI models and agents using private simulation environments and behavioral benchmarks

Pricing model

Demo

Rating

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Time to value

Requires Expertise

You can use Kimpton to test and evaluate artificial intelligence models and autonomous agents inside simulated environments. The service lets you connect any OpenAI-compatible endpoint or CLI to run behavioral benchmarks across different checkpoints. You can evaluate multi-agent coordination, test long-horizon planning, and inspect recorded trajectories from real-world simulations like financial trading floors or poker games. Independent graders score the actions and decisions your models make, and you can export comprehensive performance reports in JSON, CSV, or HTML formats to train better model checkpoints.

What Kimpton does

Run behavioral benchmarks across multiple AI models via APIRecord agent action trajectories for post-run inspection and trainingCompare benchmark scores between model checkpointsConnect custom OpenAI-compatible endpoints to evaluation suitesExport test reports in CSV, JSON, or HTML formatsDefine custom scoring rubrics and task validation criteriaGrade agent observations and decisions against explicit task rulesTest models inside live and adaptive generative environmentsInspect full recorded decision trajectories across every model runConnect any OpenAI-compatible model endpoint through CLI or APIEvaluate multi-agent coordination with shared environments and private observationsMeasure long-horizon task planning, memory, and error recoveryExport evaluation scores and detailed reports as JSON, CSV, or HTMLBenchmark domain-specific workflows such as simulated financial trading and poker