10x Science

The AI-native platform for next-generation protein characterization.

2.6Score#486 of 999 agents#8 of 16 in Scientist

Why it ranks #486

10x Science, an AI scientist from YC W26, ranks #486 of 999 AI agents and #8 of 16 in Scientist, with a score of 2.6 of 10. Data as of 3 Oct 2026.

The score adds four parts, each 0 to 10, by weight. Every point comes from public evidence. How scoring works ·

Proof 0 × 30% 0.0
Scale 3 × 30% 0.9
Momentum 3 × 25% 0.8
Autonomy 6 × 15% 0.9
= 2.6

Proof
Do customers use it? 30% of the score
0
No public claims of customers or revenue yet.
Not found: revenue or growth (+4), named customers (+3), a customer result (+2), a customer count (+2), work done at scale (+2)
Scale
Is there a real company behind it? 30% of the score
3
5 people.
- +3
  5 people on its YC page5 to 9 people
Not found: funding round in its news (+3)
Momentum
Is it shipping and growing now? 25% of the score
3
Shows hiring and a new batch.
- +2
  Hiring: 1 open roleFounding EngineerYC page
- +1
  New: YC Winter 2026
Not found: launch YC post in the last 6 months (+3), new traction claim in the last 6 months (+2), funding news in the last year (+2)
Autonomy
How much of the job does it do on its own? 15% of the score
6
Supervised agent: takes actions in other systems; a person approves key steps.
- +6
  Level 2 of 4: Supervised agentTakes actions in other systems; a person approves key steps.
What the model read
- Acts in other systems: 20% likely
- Finishes whole tasks: 22% likely
- Calls itself an agent: 3% likely
- Level 1 from the model's reading of its pages; the evidence review found, with quotes, that its AI acts in the work, so the level is 2
Level 2: Takes actions in other systems; a person approves key steps.

About 10x Science

10x Science develops frontier AI models with deep memory to redefine how scientists understand and engineer biology across the life sciences, starting with drug development.

AI-powered drug discovery is flooding the pipeline with new candidates faster than ever. But before any of them can advance to the clinic, scientists must deeply characterize the protein therapeutic to understand whether it will work. Today, that process takes months of manual, error-prone analysis that cannot keep pace with discovery. Our AI-native platform automates it, giving drug developers the confidence to advance the right candidates and stop the wrong ones early.

We have strong commercial traction with enterprise pharma customers. Our founding team built the field of next-generation protein characterization out of Carolyn Bertozzi's Nobel laureate lab at Stanford. Collectively, we have 18+ years of collective domain expertise, 47+ scientific publications, and a 2x YC Founder. We move at the highest velocity and are positioned to lead the next generation of modern AI development in the life sciences.