Sentinel AI Assistant
Sentinel is an internal AI assistant trained on a financial firm's own knowledge base — a secure, on-prem-ready copilot that gives analysts instant access to internal research and data.
Project story
The client is a financial firm whose analysts spent hours every day searching through PDFs, wikis and chat threads to find the exact number, memo or precedent they needed.
The goal of Sentinel was to build a private AI assistant that lives inside the firm and answers questions directly from the firm's own documents, with full source references.
We designed a retrieval pipeline that indexes internal PDFs, wiki pages and structured data, combined with a chat interface tuned for the firm's compliance requirements.
The assistant is powered by a curated LLM stack, an evaluation harness that continuously measures answer quality and role-based access control aligned with the firm's existing user directory.
Sensitive information never leaves the client's environment — the whole system is designed to run on-prem or in a private cloud so the firm keeps full control over data and audit logs.
Project summary
Sentinel turns a firm's own knowledge base into an instantly searchable, trustworthy AI assistant for the people who actually use it.
Analysts save hours every week and stop losing critical information inside deep folder trees.
The result is a private, auditable and continuously improving AI layer that respects the firm's security posture.
