Levocred AI

The Bloomberg of Loans

3.3Score#286 of 999 agents#6 of 14 in Investment analyst

Why it ranks #286

Levocred AI, an AI investment analyst from YC S26, ranks #286 of 999 AI agents and #6 of 14 in Investment analyst, with a score of 3.3 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 2 × 30% 0.6
Scale 1 × 30% 0.3
Momentum 6 × 25% 1.5
Autonomy 6 × 15% 0.9
= 3.3

Proof
Do customers use it? 30% of the score
2
Claims work done at scale.
- +2
  Work done at scale
  “Live across multiple credit teams, running \~$1Bn in receivables through the platform.”
  Launch YC post · 11 Aug 2026
Not found: revenue or growth (+4), named customers (+3), a customer result (+2), a customer count (+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
6
Shows a recent launch, a new claim and a new batch.
- +3
  Launched in the last 6 monthsLevocred: AI platform for credit funds, fintechs and banksLaunch YC post · 11 Aug 2026
- +2
  A new traction claim
  “Live across multiple credit teams, running \~$1Bn in receivables through the platform.”
  Launch YC post · 11 Aug 2026
- +1
  New: YC Summer 2026
Not found: open roles on YC (+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: 71% likely
- Finishes whole tasks: 35% likely
- Calls itself an agent: 92% likely
Level 2: Takes actions in other systems; a person approves key steps.

About Levocred AI

Levocred AI is the Bloomberg of loans: AI agents that run and price a lender's book. One fund cut the time to mark its book from a week to two hours and now names us as data agent, the system of record, in its loan purchase agreements.

$22T of US loans never trade because nobody can price them efficiently and defensibly. We fix pricing first by deploying inside lenders. Trading follows, the way it did for bonds.