The work, described the way we would describe it to you.

A knowledge assistant over regulated internal documents

The problem. Staff answer the same questions repeatedly from documents nobody can find, and a wrong answer has consequences.

What we do. Build the retrieval layer over the existing document store with permissions inherited from source, agree an evaluation set with the subject-matter experts, and tune until it clears the threshold. Every answer carries citations, and the system declines rather than guesses.

What you own. The pipeline, the evaluation set, the scores, and a review process for adding documents.

A back-office queue worked by an agent, with approvals

The problem. A high-volume operational queue, reconciliation, triage, onboarding checks, grows with the business and is staffed by people doing lookups.

What we do. Instrument the process first, then automate only the steps with clear rules and clean data. The agent gets scoped credentials, a human approves anything above a value threshold, and every action is traced and reversible.

What you own. The automation, the audit trail, and a measured baseline you can hold it against.

One set of numbers the whole business agrees on

The problem. Three departments report three different revenue figures, and nobody can trace either number back to a source system.

What we do. Consolidate ingestion, model the core entities once, define the metrics in a semantic layer, and put quality tests and lineage in the pipeline so a broken feed fails loudly instead of quietly.

What you own. Documented models, tested pipelines, a metric catalogue, and reporting the finance team will sign.