Inviscid AI

Real-time Physics Simulations for Industrial Facilities & Data Centers

1.5Score#885 of 999 agents#22 of 25 in Hardware engineer

Why it ranks #885

Inviscid AI, an AI hardware engineer from YC W26, ranks #885 of 999 AI agents and #22 of 25 in Hardware engineer, 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 1 × 30% 0.3
Momentum 1 × 25% 0.3
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
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
1
Shows a new batch.
- +1
  New: YC Winter 2026
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)
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: 70% likely
- Finishes whole tasks: 17% likely
- Calls itself an agent: 2% likely
Level 2: Takes actions in other systems; a person approves key steps.

About Inviscid AI

Inviscid AI builds physics-informed AI solutions that transform how buildings and data centers operate. By combining real-time IoT sensor data with computational fluid dynamics (CFD) modeling, we create digital twins that simulate building performance in real time and autonomously optimize operations.

Our platform optimizes airflow patterns and ventilation strategies to eliminate dead zones, improve air distribution, and reduce the load on mechanical systems. On the energy side, we minimize HVAC power consumption, reduce cooling costs, and lower overall operational expenses while maintaining optimal thermal comfort and indoor air quality. Beyond immediate operational efficiency, we optimize equipment scheduling and maintenance cycles by predicting system behavior under different conditions, allowing facilities managers to proactively address issues before they become problems.

Our physics first approach ensures that we're not just optimizing against historical patterns, but optimizing based on a deep understanding of how air, heat, and energy actually move through your building, enabling us to find solutions that traditional rule-based or purely data-driven systems would miss.