Oda Studio provides an AI platform that automatically extracts metadata, symbols, dimensions, and relational information from CAD and BIM drawings using vision‑language models, converting the data into structured, queryable knowledge graphs. The platform also offers generative design tools that create visualizations and alternative spatial concepts from natural‑language or image prompts, and exposes all functionality via secure REST APIs for integration into existing design and ERP workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Architects, engineers, and related professionals spend extensive manual effort extracting metadata, symbols, dimensions, and relational information from complex CAD and BIM drawings. This process is error‑prone and slows early‑stage design iteration and downstream analytics. Similar multimodal data challenges affect consulting, finance, and media teams that must combine text, tables, and visuals to derive actionable insights.
Solution
Oda Studio delivers an end‑to‑end AI platform that applies vision‑language models (VLMs) and knowledge‑graph construction to automatically parse unstructured architectural and engineering documents into structured, queryable data. The same generative AI core enables designers to produce high‑fidelity visualizations and explore alternative spatial concepts using natural‑language or image prompts, dramatically shortening the concept‑generation cycle. Integrated Retrieval‑Augmented Generation (RAG) pipelines route extracted information to downstream analytics, while automated evaluation tools align model performance with concrete business outcomes. All components are exposed via RESTful APIs and secure cloud services, allowing firms to embed AI‑driven data extraction and generative design directly into existing CAD, BIM, or ERP workflows.
Target Audience
Primary customers are architectural and engineering firms, construction contractors, and design consultancies that need automated drawing intelligence, as well as consulting and finance organizations that require multimodal document parsing and knowledge‑graph generation.
Features
- Vision‑language AI that recognizes symbols, annotations, dimensions, and title‑block metadata from rasterized or vector drawings with >95% extraction accuracy
- Automatic construction of domain‑specific knowledge graphs linking architectural elements, material specs, and construction sequences
- Text‑to‑image and image‑to‑image generative pipelines for rapid iteration of building concepts from simple prompts
- Custom data‑annotation pipelines leveraging 40+ proprietary tools and expert annotators to produce high‑quality training sets for VLM fine‑tuning
- Retrieval‑Augmented Generation (RAG) orchestration with intelligent routing, parallel execution, and intent classification for multimodal query handling
- Continuous evaluation framework that translates model metrics into KPI‑aligned business impact scores
- Scalable cloud deployment with role‑based access control, end‑to‑end encryption, and FHIR‑compatible APIs for integration with CAD/BIM and ERP systems