Playgent
Builds simulation environments (reinforcement learning environments) for testing and post-training AI agents in finance and banking, using a network of expert contributors to curate tasks, design verification rubrics, and create realistic environments.
About Playgent
When enterprise agents fail in production, the conditions that caused the failure are critical: user state, data, tool calls, and context. Without a way to recreate these conditions, teams can't fix what broke.
Playgent provides infrastructure to create high-fidelity sandbox environments for AI agents. Our environments come packaged as a single MCP url where tool calls are mocked, authentication is abstracted away, and test data can be initialized via natural language or JSON specifications.
Teams can use Playgent to reproduce production failures in safe, scoped environments that accurately reconstruct state. Finally, export runs as OTel traces from Playgent's environment to plug directly into your observability tools or RL pipelines.
Products
Production-ready RL environments for post-training AI agents on financial decision-making tasks, including tasks, verifiers, and training infrastructure.
Security and compliance
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