Outerport

EDA for Industrial Control Systems

2.3Score#602 of 999 agents#11 of 25 in Hardware engineer

Why it ranks #602

Outerport, an AI hardware engineer from YC S24, ranks #602 of 999 AI agents and #11 of 25 in Hardware engineer, with a score of 2.3 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 0 × 30% 0.0
Scale 2 × 30% 0.6
Momentum 3 × 25% 0.8
Autonomy 6 × 15% 0.9
= 2.3

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
4 people.
- +2
  4 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
3
Shows hiring.
- +3
  Hiring: 6 open rolesMember of Technical Staff, Computer Vision / Graphics, Member of Technical Staff, Product / Agents, Member of Technical Staff, Tokyo DeployedYC page
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), 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: 75% likely
- Finishes whole tasks: 36% likely
- Calls itself an agent: 97% likely
Level 2: Takes actions in other systems; a person approves key steps.

About Outerport

Building out new LNG plants, HVAC systems, or semiconductor processes rely on hundreds of iterations of feasibility testing (through simulation or real-world lab tests) where different designs (combinations of equipment) and parameters are validated. The parameters are often locked in PDFs (datasheets, wiring diagrams, PFDs/P&IDs) which take thousands of hours to convert into CSVs / JSONs, and the simulators don't have an easy API to work with. Outerport bridges the gap by finding documents from PLMs, extracting structured data from drawings, building a knowledge graph over them, and building autonomous AI agents that can fully automate this R&D process by running simulations and performing design checks.