Outerport

What do they actually do

Outerport runs a document-processing platform that converts technical PDFs, CAD/DWG drawings, P&ID/process-flow diagrams, tables, and similar engineering documents into structured, machine-readable data (text, metadata, bounding boxes, and linked components). It’s delivered as an API-first service with cloud and on‑prem/VPC deployment options, so teams can upload documents, parse them, search across results, and ask questions programmatically via REST API and SDKs homepage quickstart API reference.

Typical uses include internal technical search, compliance and audit workflows, and document generation backed by structured visual data. For difficult legacy content, they also provide human‑assisted conversion and forward‑deployed customization. Outerport states that customer data isn’t used to train third‑party models unless customers opt in, and they offer deployment controls and DPAs for enterprises homepage privacy terms.

Who are their target customer(s)

• Plant maintenance and operations engineers at manufacturers: They spend hours hunting across old drawings and scanned schematics for the right version or part spec because the content is unstructured and often only exists as scans or CAD files. They need machine-readable diagrams to power search and maintenance workflows homepage.
• AEC and MEP engineers responsible for as‑built documentation and cross‑discipline coordination: Extracting and reconciling data from many PDFs, P&IDs, and electrical schematics is slow and error‑prone, causing delays and rework. They need linked, queryable outputs from diagrams and tables homepage.
• OEMs and CAD‑heavy product teams managing large DWG/CAD libraries: Legacy CAD content is hard to search, version, and integrate with PLM/ERP systems, which slows design reuse and sourcing. They need robust parsing and metadata extraction to integrate visual assets downstream quickstart.
• Compliance, audit, and risk teams in regulated industries: They require traceability across technical documents for audits and regulatory checks, but manual review is slow and brittle. They need on‑prem/VPC options and strong data controls to operationalize extraction at scale homepage privacy.
• Enterprise AI/search teams building LLM agents over technical corpora: Agents hallucinate on raw diagrams and long technical contexts without reliable visual grounding. They need structured outputs (bounding boxes, component metadata, linked fragments) to stabilize retrieval and agent pipelines blog API reference.

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder‑led, paid pilots with maintenance/operations, AEC/MEP, or OEM teams from YC/founder networks and inbound. Deliver working parses of a small set of real drawings in 2–4 weeks and quantify time saved per lookup and reduced rework in a simple ROI summary quickstart product.
• First 50: Codify pilots into 4–6 week “maintenance” and “as‑built” kits (templates, mapping rules, acceptance checks). Run targeted outbound to plant maintenance, MEP contractors, and OEM CAD teams; add 2–3 channel partners (scan‑to‑digital vendors, engineering consultancies, Autodesk/SAP integrators) to bundle installs and services product API reference.
• First 100: Productize bespoke work into packaged offerings (on‑prem/VPC install, compliance pack, connector bundles) and hire enterprise sales/CS to run longer cycles. Expand reseller/partner network and use case studies and reference accounts to unblock RFPs; emphasize deployment/data controls (on‑prem, DPAs) for regulated buyers privacy product.

What is the rough total addressable market

Top-down context:

Relevant adjacent enterprise software categories include AEC software, PLM, CAD/3D CAD, EAM/CMMS, and predictive maintenance. Published estimates place these in the multi‑billion range: AEC software (~$11B mid‑2020s), PLM (tens of billions), 3D CAD (~$11–12B in 2024–2025), EAM (~$7.6B in 2024), and predictive maintenance (~$14B in 2025) AEC, Mordor PLM, Mordor 3D CAD, Fortune BI EAM, Grand View Research Predictive maintenance, Mordor.

Bottom-up calculation:

Outerport’s function—turning diagrams/CAD into structured, searchable visual data—is a narrow line item inside those deployments. If you sum these adjacent markets to roughly ~$95B and allocate 1–5% to diagram/CAD ingestion and structured visual data (software + integration/services), TAM lands around ~$0.95B (1%) to ~$4.8B (5%). A midpoint near ~$2.4B (2.5%) is a practical planning figure.

Assumptions:

• Only a small slice of AEC/PLM/CAD/EAM/predictive maintenance budgets is dedicated to ingestion, parsing, and integrations (single‑digit %).
• Figures are directional and overlapping; applying a small percentage avoids double‑counting across adjacent markets.
• Near‑term obtainable market is concentrated in process plants, OEMs, and large AEC firms given on‑prem/VPC and services needs.

Who are some of their notable competitors

• Autodesk Platform Services (APS): APIs to automate Revit/Fusion workflows and extract/modify model data; Autodesk Docs also offers automated drawing extraction across project lifecycles—often a DIY alternative using Autodesk’s ecosystem APS Design Automation Autodesk Docs help.
• Bentley PlantSight: Digital twin platform that aggregates engineering data and can turn P&ID documents into intelligent data sources; used for connecting design, operations, and maintenance data in asset‑heavy industries PlantSight.
• Hexagon Intergraph Smart P&ID: Enterprise P&ID environment with validation and integrations that manage intelligent P&ID data and link it with 3D models and other engineering systems—a common incumbent in process plants Smart P&ID Integration docs.
• AVEVA (P&ID and Gateway 2D Data): Tools to extract and process AVEVA P&ID DWG files with tags, attributes, and graphical data; part of broader AVEVA engineering information management suites AVEVA docs.
• Infrrd (Engineering Drawing Data Extraction): IDP vendor with a product focused on extracting structured data from engineering drawings (including P&IDs/MEP), outputting JSON/Excel for downstream systems—competes on engineering‑diagram parsing accuracy Infrrd solution.