We build semantic infrastructure that gives construction software providers the specialized and efficient AI their products need. 

Software is getting easier to build. Domain-specific intelligence is not.

The Problem:

Construction data has two structural problems.

First, much of the industry's knowledge is stored in plans, scans, tables and technical documents. These use specialized layouts, symbols and cross-references. Generic OCR models cannot read these structures reliably.

Second, BIM models, bills of quantities and product data often describe the same components. But they use different formats, terms and standards. Generic embedding models cannot reliably connect them.

Software providers must therefore accept weak results, use resource-intensive large language models, or develop specialist technology themselves.

The Solution: We train AI models that understand construction documents. Available as one API.

Our OCR makes construction documents machine-readable. Our embedding models connect information across formats. Our reranker surfaces the most relevant results.

This enables applications to retrieve information more precisely, match data across formats and access knowledge that is currently locked inside disconnected systems.

Software providers can integrate each model into their existing products through an OpenAI-compatible interface. Our specialized models require less computing power than large language models.

We are building flinq in Europe, with Europe.
That means training our model on European infrastructure and with European data. Our promise: data sovereignty without compromising on quality.