Document processing and knowledge search
We can scope extraction of fields from PDFs and forms, summaries of long documents, and search across approved internal material. The first step is a sample set: clear documents, difficult scans, missing information, and examples where an answer should not be produced.
For knowledge search, retrieval-augmented generation, or RAG, connects a model to selected source documents. We design access controls and source references so staff can inspect the material behind an answer. Retrieval does not remove the need to evaluate incorrect or incomplete results.
Integrate AI into an accountable workflow
An extraction tool may prepare fields for review before they enter a database. A report assistant may draft text from approved records while a program officer remains responsible for publication. We agree the review step and the route for uncertain or failed outputs.
The implementation plan covers model and service costs, document access, evaluation, and ongoing maintenance. We start with a bounded use case and compare the review effort with the existing process before expanding it.