❯ Trajectory raises a $45 million Series A at a $300 million valuation and opens model post-training tools to domain experts

Funding alongside a platform launchTrajectory announced its $45 million Series A on November 2 at a $300 million valuation, led by Sequoia with NVIDIA, Bessemer and Bain Capital Ventures participating. It also opened its post-training platform, which adapts existing models to business needs. Customers can train, evaluate and deploy in one place rather than assembling separate infrastructure products.

Expert judgment becomes training inputLawyers know what makes a contract review acceptable, and financial analysts have their own research standards, but that expertise does not automatically enter a general model. Trajectory lets customers supply tasks and scoring methods while handling training environments, compute orchestration and deployment. Enterprises purchase tools for turning professional judgment into model behavior without first building a complete reinforcement-learning research team.

Industry tasks already in useThe company says teams at Harvey, Rogo, Mercor and NVIDIA already train on its platform, including one customer that trained more than eight models for complex, long-running tasks in two weeks. It has also worked with NVIDIA and Harvey on legal post-training. Those examples demonstrate concrete usage, while outcomes still depend on the task, scoring standards and data rather than applying equally across industries.

Continual learning in stagesContinual Grading and Group Size 1, introduced with the platform, remain research previews. They explore extending grading from a few expert examples and training further on real production interactions. Trajectory has not disclosed a detailed allocation of the round, but is hiring. Its product sequence starts with training, evaluation and deployment tools, then experiments with ongoing improvement after launch.

▮ SIGNALLower engineering barriers to training make the ability to define good work a scarcer enterprise input; reliably converting expert standards into training signals will matter more to Trajectory’s customer value than compute access alone.