Company Intelligence

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…

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Quick Facts

  • Founded 2024
  • Headquarters San Francisco, United States
  • Country United States
  • Industry AI in Enterprise Software
  • Company Type Early
  • Status Active
  • Website Official site
  • Last Reviewed Aug 2026

Executive Summary

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.

Why It Matters

AI Electromechanical Process Engineers for Heavy Industries

Recent Developments

  1. 2024 Company founded

    Outerport was founded in 2024 per the company profile source on file.

    Source

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Industries

AI in Enterprise Software Open industry

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.

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