The problem
Discovery in biology, chemistry and materials is slow, manual and limited by scarce reproducible data
What they do
AI models plus robotic 'AI Science Factories' that design and run experiments for R&D teams
Traction No disclosed revenue; first customer cohort Oct 2025; three DOE Genesis Mission awards (Jul 2026)
Hiring trend
- Open roles
- 107
- Ops roles
- 4
- Headcount
- ~400-450
Headcount ~111 (2024) → ~383 (Mar 2026, Revelio), ~450 by Jun 2026; postings +175% in 2026
Hiring in
- Cambridge
- San Francisco
- London
Glassdoor
4.0 ★ ↗Funding
- Last round
- $350M
- Stage
- Series A
- Date
- Oct 2025
Led by Braidwell, Collective Global (NVentures in extension); Flagship Pioneering incubated
- Hiring+2107 open roles on the live job board (30+ roles = +2)
- Funding recency+1.5Series A · $350M, Oct 2025 (12 months ago): 6–12 months = +1, $100M+ round +0.5
- Traction+1.5Strong growth: No disclosed revenue; first customer cohort Oct 2025; three DOE Genesis Mission awards (Jul 2026)
- Red flags0None found in the last 24 months
- Total5.02 + 1.5 + 1.5 − 0 = 5.0 → Sprint (4.75 or more)
Distance (Unproven) is a separate read on how long the lead can last. It doesn't change the score.
Distance
Unproven · edge: learns from use
Proprietary experimental data from robotic labs could become a real edge, but no revenue or named customers yet and Periodic Labs chases the same idea with similar money.
Sources: Revenue Memo: Lila Sciences funding history (Oct 2026) ↗ · Reuters: Lila tops $1.3B valuation with Nvidia backing (Oct 2025) ↗
Last checked Oct 25, 2026