The data infrastructure
for frontier AI
Ooak Data is an applied AI research lab. We turn real company data into RL environments where AI agents learn to work in the real world.
How we do it
From real company data to RL environments
We source real enterprise data, anonymize it into digital twins, and generate reinforcement learning environments with expert-level tasks.
Sourcing
Multimodal data sourced directly from real companies through established partnerships. Documents, communications, and tools — with full organizational context preserved.
Digital Twin
Automated multimodal anonymization pipeline. Names, dates, and proprietary content are transformed — but the structure, relationships, and complexity are preserved.
RL Environments
Expert-level tasks calibrated on the latest frontier models. Multi-step, multi-tool workflows designed to expose weaknesses, not confirm strengths.
Why Ooak Data
What makes us different
Real data, not synthetic proxies
Our environments are built from real company workflows — anonymized but authentic. Synthetic benchmarks test what models can do in theory. Our data tests what they do in practice.
Multimodal from the start
Documents, conversations, project management tools, org charts. We capture the full context of how companies actually work — not text-only with modalities bolted on later.
Calibrated for the frontier
Our tasks are designed to challenge the latest models. As models improve, our environments evolve. You are always testing at the edge of capability.
Built for agents, not chatbots
Most evaluation frameworks test single-turn Q&A. We build multi-step, multi-tool environments that test what matters: can your agent actually complete a workflow?
Research
We publish what we learn
Why synthetic benchmarks are holding AI back
The AI industry over-indexes on synthetic benchmarks that don't reflect real-world complexity.
Read essay →The data problem in agentic AI
AI agents need fundamentally different data than chatbots — and we don't have it yet.
Read essay →From sandbox to production: the gap nobody talks about
80% of AI projects fail in production. The problem is not the models.
Read essay →Who we serve
Built for the teams pushing AI forward
Frontier AI Labs
RL environments grounded in real enterprise data that push your models beyond synthetic benchmarks.
Enterprise AI Teams
Digital twins that let you evaluate agent performance against realistic company environments before going to production.
AI Startups
Real-world evaluation infrastructure without building data pipelines from scratch.
Building AI that works in the real world starts with real-world data
Tell us what you are working on. We will show you how our data infrastructure can help.
Get in touch