Enterprise AI Knowledge Platform
A multinational professional services firm with 15,000 employees had knowledge scattered across wikis, document repositories, email threads, Slack channels and project management tools. Staff spent an average of 2.5 hours per day searching for information, and new hires took three to four months to become productive because there was no centralized way to learn internal processes.
Challenge
A multinational professional services firm with 15,000 employees had knowledge scattered across wikis, document repositories, email threads, Slack channels and project management tools. Staff spent an average of 2.5 hours per day searching for information, and new hires took three to four months to become productive because there was no centralized way to learn internal processes.
Solution
We built an AI-powered enterprise knowledge platform that indexed over 2 million internal documents and connected to 12 source systems. The system used Retrieval-Augmented Generation to deliver precise answers with citations, ranked by relevance to the user's role and department. We implemented a feedback loop where users could rate responses, which continuously improved retrieval quality. The platform included role-based access control so sensitive documents stayed visible only to authorized teams.
Outcome
Average search time dropped from 15 minutes to 45 seconds. The knowledge base served 8,000 active users in the first quarter. New hire ramp time shortened from 14 weeks to 6 weeks. The firm estimated $2.4 million in annual productivity savings. Support tickets related to internal process questions dropped 62%.
Technology Stack
Architecture
Frontend → API Gateway → RAG Pipeline → Vector DB → LLM → ResponseReady to Build Something Exceptional?
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