Propaya

1.8Score#781 of 999 agents#14 of 27 in Document processor

Why it ranks #781

Propaya, an AI document processor from YC S24, ranks #781 of 999 AI agents and #14 of 27 in Document processor, with a score of 1.8 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 0 × 25% 0.0
Autonomy 6 × 15% 0.9
= 1.8

Proof
Do customers use it? 30% of the score
2
Claims a customer result.
- +2
  A customer result
  “Propaya customers save 90% of lease review processing time and cost compared to before.”
  Launch YC post · 5 Dec 2024
Not found: revenue or growth (+4), named customers (+3), 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 Summer 2024) (+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: 37% likely
- Finishes whole tasks: 15% 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 Propaya

Propaya is an AI-powered commercial real estate intelligence platform that transforms leases and property documents into structured, actionable data. It extracts key terms, obligations, costs, and critical dates with source citations, while identifying legal, operational, environmental, and biological property-risk signals. Teams can customize risk taxonomies, track portfolio-level issues, export structured data, and route flagged findings to property managers, legal teams, or domain specialists for review.