GYRATE Intelligence transforms expert knowledge, physics, simulations, and real-world manufacturing data into AI training datasets, reinforcement learning environments, and evaluation systems that advance AI's ability to engineer the physical world.
It is both an external product sold to AI developers and the intelligence infrastructure powering GYRATE's own artificial engineers.
AI labs, model developers and engineering-software companies that need their models to design real hardware, not just describe it.
To become the standard AI is trained and measured against on physical engineering, and to publish a public leaderboard every lab is judged on.
Expert-generated engineering training datasets
Physics and simulation-based reinforcement learning environments
CAD, CAE, electronics, manufacturing and robotics agent training tasks
Engineering benchmarks, evaluations and automated verification
Experimentally validated engineering and manufacturing feedback
Engineering physical systems cannot be reduced to generating plausible text. A model can read every textbook about motors, aircraft or manufacturing and still lack the ability to design something that survives real loads, tolerances, temperatures, materials, failure modes and production constraints.
Engineering experts supply tasks, workflows and verified design artifacts.
CAD, CAE, electronics and manufacturing environments the AI can act in.
Every task has traceable inputs and artifacts that can be run and checked.
Automated checks, expert review, and critical failures that are never averaged away.
When feasible, experimental results and factory data confirm what simulation predicts.
Simulation-only demonstrations are not enough to claim physical reliability. Human engineering approval and independent testing remain essential for consequential applications.
A benchmark that asks AI agents to turn electromechanical engineering requirements into verifiable engineering outputs. Example task: design and validate a robotic joint actuator from a detailed performance specification.
Illustrative benchmark design with proposed evaluation weights, not measured results. Critical safety or requirement failures trigger an overall failure rather than being averaged away. The plan is a publicly reproducible leaderboard plus private holdout evaluations.
Custom expert datasets, licensed datasets, and engineering task trajectories.
For AI laboratories and model developers.
Usage-based access and annual licenses for physics and engineering agent environments.
For AI laboratories and agent startups.
Recurring benchmark access, model testing, and engineering capability assessments.
For model developers and CAD/CAE vendors.
Factory measurements, test results and process data reveal how designs behave outside simulation. With appropriate permissions and data governance, that information supports GYRATE Intelligence, and the improved AI drives more engineering and manufacturing.
GYRATE owns or licenses every training dataset appropriately, segregates confidential customer information, and keeps controlled technical data out of unrestricted training systems.
If you develop AI models, agents or engineering software and want expert-verified engineering data, environments or evaluations, we would like to hear from you.
Talk to Us