AI Governance Safety & Evaluation Enterprise Only

Polymath

Realistic simulation environments for training long-horizon autonomous AI agents

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PricingEnterprise Only
Starting priceContact sales
Free planNo
Free trialYes
APINo
Open sourceNo
DeploymentCloud
Last verifiedJuly 30, 2026
Overview

Tool overview

Polymath is listed under AI Governance Safety & Evaluation AI tools.

Summary

What is Polymath?

Polymath builds simulated worlds, tasks, and verifiers for training and evaluating autonomous agents. Its environments reproduce production systems and multi-tool workflows so model labs can measure planning, deployment, debugging, and sustained execution.

Best fit

Best for

Frontier model labs training and evaluating autonomous agents

Audience

Who is it for?

AI model labsAgent researchersEvaluation teamsReinforcement-learning engineersSoftware-agent developers
Recommendation

Decision note

Suitable for evaluation after confirming final commercial terms, controlled-field cleanup, permissions, data handling, and edit-screen aliases. Keep Needs Review enabled until a human verifies the published profile.

Capabilities

Key features

Realistic environments with running applications and evolving state

Long-horizon tasks spanning hours or days of work

Verifiers for objective outcomes and partial credit

Multi-tool workflows exposed through MCP

Production services, traffic, logs, and alerting

Horizon-SWE benchmark for end-to-end software engineering

Workflows

Use cases

Training agents on production workflows

Evaluating long-horizon software engineering

Testing multi-tool planning and judgment

Generating reinforcement-learning rollouts

Building custom environments for model labs

Strengths

Pros

  • Focused on realistic agent behavior beyond code generation
  • Published benchmark methodology and model results
  • Supports verifiable outcome-based evaluation
  • Team has frontier-model and infrastructure experience
Considerations

Limitations

Simulation performance may not transfer directly to every production environment. Model labs should review task realism, verifier design, data provenance, hidden assumptions, security boundaries, and statistical uncertainty before using scores for deployment decisions.

Cost

Pricing details

Pricing modelEnterprise Only
Starting priceContact sales
Free planNo
Free trialYes
Pricing context

Billing options

Custom research or service contract

Pricing context

Pricing note

Polymath works directly with leading model labs on custom environments and services. No public self-service plans, standard rates, free commercial tier, or trial were confirmed.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

Issue trackers

Messaging tools

Knowledge bases

CI/CD

Sentry

Logs and metrics

Specs

Technical details

PlatformsWeb
Multilingual supportUnknown
Login requiredNo
Open sourceNo
DeploymentCloud
CompanyPolymath
Launch year2026
Current versionHorizon-SWE
Models / versionsHorizon-SWE Polymath environments
Editions / plansFree, Basic, Professional, Organization, and Custom plans
Data confidenceHigh
Last verifiedJuly 30, 2026
Documentation → Release notes → Data source →
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Answers

Frequently asked questions

Polymath builds simulated worlds, tasks, and verifiers for training and evaluating autonomous agents. Its environments reproduce production systems and multi-tool workflows so model labs can measure planning, deployment, debugging, and sustained execution.
Frontier model labs training and evaluating autonomous agents
The listed pricing model for Polymath is Enterprise only. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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