Trajectory raises $45M Series A to democratize AI model training
The Stanford-founded startup's continual learning platform lets nontechnical experts improve AI models from real-world feedback without hiring research teams.
What to know
- Trajectory built a platform that automates AI model improvement through user feedback, eliminating the need for expensive in-house research teams or consultants in specialized fields.
- The $45M Series A at $300M valuation signals strong investor confidence in the continual learning market, with participation from both traditional VCs and AI infrastructure players like Nvidia.
- The startup enters a crowded competitive landscape including Thinking Machines Lab (founded by former OpenAI CTO Mira Murati), Applied Compute ($3.25B valuation), and Prime Intellect.
- Trajectory emphasizes human oversight in AI training as a safety feature, distinguishing its approach from autonomous self-improvement systems that carry uncontrolled risk.
“keeping humans involved in the training process makes Trajectory's approach safer, since autonomous self-improvement could lead to unintended or even dangerous outcomes”
Michael Elabd, Trajectory co-founder · TechCrunch ↗
Ronak Malde Trajectory co-founderMichael Elabd Trajectory co-founderArjun Karanam Trajectory co-founderSequoia Lead investor
How it unfolded 1 development · click the chart to see its coverage articlesposts
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Co-founder argues human oversight makes approach safer than autonomous AI self-improvement
Michael Elabd positions Trajectory's continual learning as distinct from recursive self-improvement (RSI) because humans remain involved in the training process, reducing risks of unintended or dangerous outcomes from autonomous AI capability improvement.
“But what the economy values is someone who worked on the job for 30 years…”
— Ronak Malde, Trajectory co-founder · source -
first by TechCrunch, 5d ago
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Trajectory raised a $45M Series A led by Sequoia and opened its continual learning platform 🔁 AI models keep improving from real product feedback. #AI #LLM #Startups
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Trajectory raises $45M at a $300M valuation to help nontechnical experts train AI models. Its platform uses feedback to improve open-source models for specialized tasks, with humans guiding the process. Source:
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提案書に入れた赤字も、AI改善の材料に。$45 millionを調達したTrajectoryは、現場の評価をモデルの再学習につなぎます。 僕ならまず「なぜ直したか」を残しますが、皆さんは修正理由まで記録していますか？
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background
Trajectory opens post-training platform to public — The startup is making its continual learning platform publicly available, allowing businesses to connect open source AI models to their applications and automatically retrain them based on performance feedback. Early adopters include legal AI platform Harvey, financial analysis tool Rogo, and Nvidia.
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background
Trajectory announces $45M Series A at $300M valuation — The 18-person startup raised funding led by Sequoia, with participation from Nvidia, Bessemer Venture Partners, and Bain Capital Ventures. Founded about a year ago by three Stanford classmates with backgrounds at Google DeepMind and Apple, Trajectory develops a continual learning platform for AI model post-training.