GoKawiilTrajectory raises $45M Series A to automate AI fine-tuning for specialists
Trajectory, an 18-person startup founded by three Stanford alumni, has raised $45 million in a Series A round at a $300 million valuation, led by Sequoia with participation from Nvidia, Bessemer Venture Partners, and Bain Capital Ventures. The platform lets businesses connect open source AI models to their applications, collecting feedback that is used to retrain and improve those models for specialized tasks over time. Legal tech company Harvey and financial analysis firm Rogo are already using the platform to post-train open source models for their respective industries.
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The funding suggests investor confidence in 'continual learning' as a cheaper alternative to hiring internal AI research teams or forward-deployed engineers for fine-tuning models in fields like law and finance. Co-founder Ronak Malde's comparison of base AI models to an inexperienced new hire frames the company's pitch: automating the accumulation of job-specific expertise that currently requires costly manual intervention. If successful, this approach could lower the barrier for nontechnical domain experts to customize AI systems themselves, potentially reshaping how specialized AI tools are built and maintained.
- Trajectory raised $45M in a Series A at a $300M valuation, led by Sequoia with Nvidia, Bessemer, and Bain Capital Ventures participating.
- The startup automates fine-tuning of open source AI models using real-world feedback, aiming to replace costly manual retraining processes.
- Harvey and Rogo are current customers using the platform to adapt models for legal and financial analysis tasks.
Source: techcrunch.com — Marina Temkin, 2026-11-02
Published there as: “Trajectory raises $45M to make AI model training accessible to nontechnical experts”
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