Ooak Data

Generate realistic reinforcement learning environments and evaluation datasets from enterprise workflows

Pricing model

Demo

Rating

★ People love it

Time to value

Requires Expertise

You can use Ooak Data to convert your organization's internal workflows into realistic training environments for autonomous agents. The system extracts multimodal enterprise data from applications like Slack, Jira, and Notion, and anonymizes sensitive records while maintaining structural relationships. Teams can then deploy agents into simulated digital twin environments to test complex, multi-step actions across different workplace tools. This allows frontier labs and enterprise engineering teams to benchmark agent reliability, expose flaws, and validate operational safety before deploying agents into real-world production.

What Ooak Data does

Anonymize sensitive enterprise data from workplace communicationsBuild reinforcement learning environments from corporate documentationEvaluate multi-step agent actions across multiple workplace toolsBenchmark AI agent reasoning against frontier model baselinesCreate digital twins of company software setups for model trainingTest agent performance on complex business workflowsAutomated multimodal anonymization pipeline for enterprise communications and docsDigital twin generation preserving organizational context and data relationshipsReinforcement learning environments calibrated against frontier modelsMulti-tool workflow testing across applications like Jira, Notion, and SlackMulti-step task generation to uncover edge-case failures in agent reasoningCross-application coherence tracking across documents and message histories