Multi-system data unification & an internal knowledge agent
The problem is one almost every SMB recognizes: operations teams spending hours a day cross-referencing data isolated across disparate software, databases and unorganized documents. Every answer exists somewhere. Nobody can say exactly where, and the person who could is on vacation.
We unify the fragments into one governed, vector-indexed knowledge base and put a retrieval-augmented agent on top of it, inside the chat tools the team already uses. Strict data-boundary rules are set during the audit, so the same build holds up in a HIPAA or FINRA shop as well as it does in a consumer brand.
Shadowed staff through their real workflows to map exactly where data access bottlenecks — which lookups burn hours, which answers get guessed. Strict data-boundary rules were established up front, built to HIPAA and FINRA standards where they apply.
Pipelines for structured and unstructured data — databases, documents, tickets, drives — feeding clean, vector-indexed data into custom retrieval-augmented agent workflows.
The scorecard is tested against hundreds of real business queries the client chose, graded for factual accuracy, data access controls and latency, with thresholds agreed before go-live.
Integrated directly into the team's daily communication channels — Slack and Teams — and launched with a company-wide workshop and reference guides, so adoption starts on day one.
Continuous logging of unanswered and escalated queries, reviewed against the same scorecard the system shipped with. Production tells you where the index disagrees with the questions people actually ask.
Escalations become new scored cases, and retrieval paths are retuned weekly against them. Each pass sharpens the index and shrinks the escalation rate.