A.5 · Artificial Intelligence & Machine Learning
Natural Language Processing & Document Intelligence
Retrieval that cites its source, across contracts, forms, and archives
What we build
Retrieval and extraction systems over document estates that were never designed to be queried. Layout-aware parsing of PDFs, scans, forms, and technical drawings, table and field extraction with per-field confidence, hybrid vector and lexical retrieval with cross-encoder re-ranking, chunking tuned to document structure rather than character count, answers bound to a citable source page, and incremental re-indexing as the corpus changes.
Capabilities
- Layout-aware parsing of PDFs, scans, forms, invoices, and technical drawings
- Table and field extraction with a confidence score on every value
- Hybrid vector and lexical retrieval with cross-encoder re-ranking
- Answers bound to a citable source page, and no answer returned when evidence is thin
- Classification, entity extraction, summarisation, and translation over the same corpus
- Incremental re-indexing and permission-aware retrieval for every reader
Related services
How it connects
Where it sits in the stack.
This service, and the two it hands off to. None of them can be optimised alone.
NLP & Document AI
Retrieval and extraction systems over document estates that were never designed to be queried.
Generative AI & LLMs
Production systems built on large language models, hosted or self-hosted.
AI & Machine Learning · see serviceAgentic AI & Copilots
Multi-step agent runtimes wired into the systems an organisation actually runs on.
AI & Machine Learning · see serviceBring us the whole problem.
Tell us where the work is stuck, whether that is a model that never reached production, an application nobody can change, a data platform nobody trusts, or a plant the business cannot see. An engineer replies with a first read, not a sales deck.