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AI infrastructure

DeepSim, Inc.

DeepSim is building an AI physics simulator. We are currently developing the only thermal simulator to meet AI chip design needs and are validating our tool with Intel. We are a team of three electrical engineering PhDs from Stanford with backgrounds in semiconductor fabrication and design.

sources
1
Evidence entries preserved.
affiliations
1
Y Combinator
competitors
6
Mapped from High Signal graph features.
status
generated
D1 lookup
last updated
2026-07-15
16:41 UTC
source evidence
Why this company exists here

Y Combinator

yc-company-directory #2843

DeepSim is building an AI physics simulator. We are currently developing the only thermal simulator to meet AI chip design needs and are validating our tool with Intel. We are a team of three electrical engineering PhDs from Stanford with backgrounds in semiconductor fabrication and design.

source
generated read
High Signal interpretation

DeepSim, Inc. is classified as AI infrastructure from source descriptions and fund-directory context. Similar companies below are ranked from offline product facets and meaningful description overlap; category and source affiliation can only strengthen an existing product match. For lookup-created rows, the profile starts as pending enrichment until deeper source collection runs.

offline extraction
Product facets
AI physics simulatorsemiconductor fabrication and designthermal simulatorDeepSim
mapping method
Similarity graph

Local clusters rerank extracted product concepts and description terms. The generated graph remains the fallback for sparse descriptions: offline reciprocal product-similarity graph: extracted concepts + description terms + bounded category/affiliation boosts. Minimum fallback score: 0; max competitors: 6.

discovery cluster

Companies similar to DeepSim, Inc.

AI infrastructure · 6 peers

A deterministic local cluster built from offline product facets and meaningful description terms. Category and selected-institution affiliation provide bounded tie-breaks. Open any peer to continue exploring its cluster.

Analog Craft

match 47

AI-driven chip design that compresses semiconductor timelines from months to weeks.

shared extracted concept terms: design, semiconductor; shared product terms: chip, design, semiconductor; same category: AI infrastructure

Waypoint Transit

match 46

Waypoint Transit is an AI city planner that generates civil infrastructure studies. Cities spend $50B/year on planning. With Waypoint, cities can generate reports in months rather than years, and at 30% of the cost. Varun and Ryan met at Stanford, where they graduated with degrees in CS and EE respectively. Before founding Waypoint, Varun worked on AI at Microsoft and Ryan worked on chip design at Apple. US cities are facing three major crises: congestion, budget deficits, and climate change. At

shared extracted concept terms: design; shared product terms: chip, design, three, stanford; same category: AI infrastructure; shared affiliation: Y Combinator

Outerport

match 43

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

shared extracted concept terms: semiconductor; shared product terms: simulator, design, validat, semiconductor; shared affiliation: Y Combinator

Confluence Labs

match 38

While modern AI excels in any area you can collect a lot of data for, it struggles in areas where data is sparse or costly to attain. Designing new molecules, discovering new physics, and engineering new materials are all domains where collecting data is extremely costly. We dream of a world where AI accelerates research in all of these domains and creates a more abundant future for humanity, but the current technology is not there. That’s why we started Confluence Labs. We are building AI that

shared extracted concept terms: design; shared product terms: design, physic, engineer; same category: AI infrastructure; shared affiliation: Y Combinator

Discovered Materials

match 35

We use AI to discover new materials for the semiconductor industry - specifically datacenters and fabs. Finding novel materials today takes 10+ years of lab work. We aim to compress that timeline to months, using a swarm of AI agents. Akash completed his PhD at Stanford on material discovery for semiconductors. The materials he discovered for nanoscale interconnects have been adopted into the roadmaps of Intel and TSMC. Advaith was the founding applied scientist at Persona AI (acquired by Luma L

shared extracted concept terms: semiconductor; shared product terms: intel, stanford, semiconductor; shared affiliation: Y Combinator

Medium Biosciences

match 30

We turn advances in AI and protein design into experimentally validated molecular tools, partnering with research teams and diagnostic developers to deliver high-performance affinity reagents in weeks, not months.

shared extracted concept terms: design; shared product terms: design, validat; same category: AI infrastructure; shared affiliation: Y Combinator