Frekil

RWE Generation in minutes

1.2Score#940 of 999 agents#16 of 16 in Scientist

Why it ranks #940

Frekil, an AI scientist from YC Sp25, ranks #940 of 999 AI agents and #16 of 16 in Scientist, with a score of 1.2 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 1 × 30% 0.3
Momentum 0 × 25% 0.0
Autonomy 6 × 15% 0.9
= 1.2

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
1
2 people.
- +1
  2 people on its YC page2 people
Not found: funding round in its news (+3)
Momentum
Is it shipping and growing now? 25% of the score
0
Nothing new in the last 6 months.
Not found: launch YC post in the last 6 months (+3), open roles on YC (+2), new traction claim in the last 6 months (+2), funding news in the last year (+2), a batch in the last year (it is YC Spring 2025) (+1)
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: 40% likely
- Finishes whole tasks: 37% 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 Frekil

Today, it takes months to understand how drugs perform in the real world, delaying safety insights and leaving patients exposed to unknown risks and benefits for far too long. Frekil turns that months-long process into minutes, with full auditability and scientific rigor.

Frekil accelerates real world evidence (RWE) generation for life sciences companies on their own clinical data from months to minutes. It connects to fragmented clinical data (EHR, Claims, etc.) and lets teams run end-to-end studies from study design, cohort extraction to SAP, statistical analysis, and final reports.