We build retrieval systems that answer from your approved sources, cite the passage behind every answer, and are tested before anyone relies on them.
A model on its own will answer anything, confidently and sometimes wrongly. Retrieval fixes that by making it read your material first, so an answer either comes from a document you approved or does not come at all.
It runs in your environment, on your accounts. We build an evaluation set from real questions your people ask, score the system against it before launch, and hand over the set so you can rerun it yourself.
Three systems answering from a firm's own material, each citing the document behind the answer.
Financial services
A financial services firm gave staff an assistant that answers policy questions in plain language, with every answer citing the compliance document it came from.
Read the case study: Answering policy questions from a firm's own documents
Professional services
A consulting firm answers recurring client questions around the clock from its own guides, in its own tone, without pulling the team off client work.
Read the case study: Building a self-service client experience with a branded assistant
Professional services
A consulting firm made the knowledge held by its senior people searchable by everyone, using the playbooks and templates they had already written.
Read the case study: Capturing senior consultants' knowledge in an internal assistant
Search returns documents and leaves the reading to you. Copilot answers across whatever a licence gives it, which is rarely the same set as the documents your firm treats as authoritative. This answers from sources you nominated, and shows the passage it used, so a reviewer can check it in seconds.
Usually not. Fine-tuning teaches a model a style or a format. It cannot cite anything, and it cannot forget a document you withdraw. Retrieval reads the current version at the moment of the question, which is what a policy or a matter file needs.
We build an evaluation set from questions your people already ask, agree the correct answer for each with someone who owns the subject, and score the system against it before launch. You keep the set, so the same score can be rerun after any change.
It says so. A system that answers everything is the failure mode rather than the goal, so the out of scope questions are agreed in writing and the system declines them instead of reaching for the model's general knowledge.
Tell us which documents hold the answers and who is allowed to read them. We will tell you what a system over them would take, and how we would prove it works.