conv.

All stories
AIQuiet 6d · day 6

Trajectory launches self-serve post-training platform with $45M Sequoia Series A

Ronak Malde's startup aims to democratize AI model customization by letting companies fine-tune models on their own data without scarce research talent.

newest coverage 5d agosummary written 5d ago2 pieces20 likes & upvotes4 comments XNewswires

What to know

  • Trajectory's self-serve platform automates post-training, the labor-intensive step where AI models are customized for specific business use cases, using techniques like Continual Grading.
  • The $45M Series A at $300M valuation includes major infrastructure players (NVIDIA, Sequoia, Bessemer, Bain), indicating conviction that post-training automation is a significant market.
  • The startup directly competes with Applied Compute and Thinking Machines Lab's Tinker, while companies like Harvey, Rogo, Mercor, and NVIDIA are already testing its claims.

“Post-training is where general models become useful for a specific company's work, and it still usually requires scarce research talent.”

RuntimeWire, Technology publication · RuntimeWire ↗

Ronak Malde Trajectory founder and CEOSequoia Capital Lead investorNVIDIA Series A investor

Trajectory launches self-serve post-training platform with $45M Sequoia Series A
x.com

How it unfolded 1 development · click the chart to see its coverage articlesposts

Peak 1 piece in two hours at Nov 2, 3 PM; 2 pieces over 6 days (1 article · 1 post) Nov 2, 3 PM — 1 piece · 1 post — X 1Nov 2, 5 PM — 1 piece · 1 article — Newswires 1Nov 2, 7 PM — quietNov 2, 9 PM — quietNov 2, 11 PM — quietNov 3, 1 AM — quietNov 3, 3 AM — quietNov 3, 5 AM — quietNov 3, 7 AM — quietNov 3, 9 AM — quietNov 3, 11 AM — quietNov 3, 1 PM — quietNov 3, 3 PM — quietNov 3, 5 PM — quietNov 3, 7 PM — quietNov 3, 9 PM — quietNov 3, 11 PM — quietNov 4, 1 AM — quietNov 4, 3 AM — quietNov 4, 5 AM — quietNov 4, 7 AM — quietNov 4, 9 AM — quietNov 4, 11 AM — quietNov 4, 1 PM — quietNov 4, 3 PM — quietNov 4, 5 PM — quietNov 4, 7 PM — quietNov 4, 9 PM — quietNov 4, 11 PM — quietNov 5, 1 AM — quietNov 5, 3 AM — quietNov 5, 5 AM — quietNov 5, 7 AM — quietNov 5, 9 AM — quietNov 5, 11 AM — quietNov 5, 1 PM — quietNov 5, 3 PM — quietNov 5, 5 PM — quietNov 5, 7 PM — quietNov 5, 9 PM — quietNov 5, 11 PM — quietNov 6, 1 AM — quietNov 6, 3 AM — quietNov 6, 5 AM — quietNov 6, 7 AM — quietNov 6, 9 AM — quietNov 6, 11 AM — quietNov 6, 1 PM — quietNov 6, 3 PM — quietNov 6, 5 PM — quietNov 6, 7 PM — quietNov 6, 9 PM — quietNov 6, 11 PM — quietYesterday, 1 AM — quietYesterday, 3 AM — quietYesterday, 5 AM — quietYesterday, 7 AM — quietYesterday, 9 AM — quietYesterday, 11 AM — quietYesterday, 1 PM — quietYesterday, 3 PM — quietYesterday, 5 PM — quietYesterday, 7 PM — quietYesterday, 9 PM — quietYesterday, 11 PM — quietToday, 1 AM — quietToday, 3 AM — quietToday, 5 AM — quietToday, 7 AM — quietToday, 9 AM — quiet 1
Nov 3Nov 4Nov 5Nov 6yesterdaynow · 10:36 AM ET
  1. 1

    Unusual Whales highlights shift in AI model control

    An X account frames Trajectory's launch as a decentralization of AI behavior definition, moving decision-making beyond the handful of major labs.

    “Until now, how AI behaves has been decided by a handful of labs. They pick the data, write the rewards and define what "good" means. Trajectory launched to change that.”
    — @unusual_whales

    • Until now, how AI behaves has been decided by a handful of labs. They pick the data, write the rewards and define what “good” means. Trajectory launched to change that. The Trajectory platform is the first self-serve product for post-training AI models on production data. You

      @unusual_whalesX5d ago20▲view on X ↗
  2. background

    Trajectory closes $45M Series A at $300M valuation — The round was led by Sequoia Capital and included NVIDIA, Bessemer Venture Partners, and Bain Capital Ventures, signaling investor confidence in the post-training automation market.

  3. background

    Trajectory launches self-serve post-training platform — Ronak Malde's startup opened its self-serve platform for post-training AI models on production data, targeting the labor-intensive step where general models become useful for specific company applications.