Corgi Labs

AI to increase payment acceptance and reduce fraud for businesses

1.5Score#876 of 999 agents#15 of 15 in Financial-crime analyst

Why it ranks #876

Corgi Labs, an AI financial-crime analyst from YC W23, ranks #876 of 999 AI agents and #15 of 15 in Financial-crime analyst, with a score of 1.5 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 2 × 30% 0.6
Momentum 0 × 25% 0.0
Autonomy 6 × 15% 0.9
= 1.5

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
2
3 people.
- +2
  3 people on its YC page3 or 4 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 Winter 2023) (+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: 48% likely
- Finishes whole tasks: 10% likely
- Calls itself an agent: 2% 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 Corgi Labs

End-to-end suite of fraud detection and prevention solutions, including an analytics product to monitor and understand dispute + fraud metrics, an AI product which highlights transactions for merchants to follow up on, and an AI solution to recommend rules that can be implemented in payment provider platforms (Stripe, Shopify, Adyen) to proactively reduce dispute + fraud rates.