AI engineering scientists - search PLMs, read drawings, run simulation
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.
Total raised
$500K
Last stage
Seed
Investors
Towaki Takikawa
Ex-Research Scientist at NVIDIA, working on R&D for simulation (neural fields, 3D computer vision, 3D generative models). Previously worked in robotics (systems engineering / electro-mechanical design) and manufacturing (operating various CNC machines 😎).
Allen Wang
I previously worked at Tome (LLMs / diffusion models for slide decks), Embark (computer vision for self-driving), Meta (data science), LinkedIn (graph analytics). CS and math alum from UWaterloo.
LinkedInTowaki Takikawa
Ex-Research Scientist at NVIDIA, working on R&D for simulation (neural fields, 3D computer vision, 3D generative models). Previously worked in robotics (systems engineering / electro-mechanical design) and manufacturing (operating various CNC machines 😎).
LinkedInNo applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.