Finance
Can models make sound financial decisions as markets change?
Kimpton runs models inside environments and records the resulting trajectories for evaluation and training.
Kimpton
The new model returns to the environment.
Run benchmarks and environments across providers through a CLI or API. Choose a model route or connect your own OpenAI-compatible chat endpoint.
Select a versioned evaluation and review compatibility and cost before running. Export scores and reports as JSON, CSV, or HTML.
Read the EvalRouter docsWe build private environments and benchmarks to evaluate your models. Define the task and scoring, then compare checkpoints using outcomes and recorded trajectories.
Measure planning, memory, and recovery across extended action sequences.
Test strategic adaptation and coordination when agents share an environment with private observations.
Our research examines action-conditioned predictions of future state, separately from an agent’s ability to complete a task.
Run your model in generative environments with persistent world state. Scored results adjust the mix of validated tasks and difficulty levels.
Generated events must satisfy explicit rules before they change world state. Independent graders score the recorded observations, actions, and outcomes.
Discuss adaptive environmentsThese domains require decisions under uncertainty and feedback that arrives over time. Our work spans private evaluations and applied research.
Can models make sound financial decisions as markets change?
Can models make biological predictions that hold up in experiments?
Can models predict the consequences of their actions in the physical world?
Can models reliably carry complex work through to completion?
Can models defend systems against threats they have never seen?
Can models meet energy demand while managing cost and reliability?
Define the capability or workflow you need to evaluate. We work with you to specify the tasks, scoring, and validation criteria, then build the environment or benchmark around them.