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§ Private Profile · San Francisco, CA, USA
Turn diagrams, technical documents, and CAD into structured data
Outerport has raised $500K across 1 funding round.
Key people at Outerport.
Outerport was founded in 2024 by Allen Wang (Co-founder / CTO) and Towaki Takikawa (Co-Founder / CEO).
Outerport has raised $500K in total across 1 funding round.
Extract structured data from documents, tables, P&ID diagrams, process flow diagrams, GD&T drawings, electrical CAD, blueprints, and more. Build AI agents with tools that help them understand and measure the world.
Outerport has raised $500K across 1 funding round. Most recently, it raised $500K Seed in September 2024.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Sep 1, 2024 | $500K Seed | — | Flex Capital, Y Combinator, Balaji Srinivasan | Announced |
Key people at Outerport.
Outerport was founded in 2024 by Allen Wang (Co-founder / CTO) and Towaki Takikawa (Co-Founder / CEO).
Outerport has raised $500K in total across 1 funding round.
Outerport's investors include Flex Capital, Y Combinator, Balaji Srinivasan.
Outerport builds advanced AI-powered tools that convert complex technical documents, diagrams, and CAD files into structured, queryable data. Their product serves enterprises and startups that rely on engineering documents such as P&ID diagrams, process flow diagrams, GD&T drawings, and electrical CAD. By transforming these traditionally unstructured assets into formats readable by large language models (LLMs) and AI agents, Outerport solves the problem of inaccessible technical data, enabling better search, automation, and AI-driven insights. This capability supports industries like manufacturing, engineering, and digital twin creation, helping clients reduce operational friction and improve AI deployment efficiency.
For an investment firm, Outerport’s mission centers on enabling AI agents to understand and measure the physical and technical world through structured data extraction. Their investment philosophy likely focuses on frontier AI infrastructure and enterprise AI tools, targeting sectors such as industrial automation, AI model deployment, and digital engineering. Outerport impacts the startup ecosystem by pushing forward AI applications in technical domains traditionally underserved by AI, bridging the gap between complex engineering data and modern AI workflows.
Outerport was founded in 2024 by Towaki Takikawa and Allen Wang. Takikawa brings a background as a research scientist at NVIDIA, specializing in AI for digital twins, 3D reconstruction, and generative models, with prior experience in autonomous driving and manufacturing platforms. Wang has experience in LLMs, diffusion models, computer vision, and data science from roles at Tome, Embark, Meta, and LinkedIn. The idea emerged from their combined expertise in AI and technical domains, recognizing the challenge of making complex engineering documents accessible and actionable by AI systems. Early traction includes participation in Y Combinator’s Summer 2024 batch and securing enterprise clients among Fortune 500 companies and financial institutions.
Outerport rides the trend of AI democratization and enterprise AI adoption, particularly in industrial and engineering sectors where data is complex and traditionally siloed. The timing is critical as large AI models grow in size and complexity, creating new infrastructure challenges like cold starts and inefficient GPU utilization. Outerport addresses these market forces by enabling efficient deployment and integration of large AI models with technical data, facilitating the rise of compound AI systems that combine multiple models and data sources. Their work influences the broader ecosystem by enabling AI agents to interact with real-world engineering data, accelerating digital transformation in manufacturing, infrastructure, and compliance.
Looking ahead, Outerport is poised to expand its platform capabilities, deepen enterprise integrations, and refine its AI model deployment tools to support increasingly complex AI workflows. Trends shaping their journey include the growth of multi-LLM systems, AI-driven automation in engineering, and the need for scalable AI infrastructure. Their influence may evolve from a niche technical document processor to a foundational AI infrastructure provider for industrial AI applications, driving cost efficiencies and unlocking new AI use cases in technical domains. Outerport’s mission to make every diagram and document queryable ties back to their core vision of enabling AI to truly understand and measure the physical world.
