Professional services firms run on knowledge. But when that knowledge is scattered across email threads, shared drives, project management tools, and legacy databases, finding the right information at the right time becomes a daily frustration.
The Challenge
This mid-sized services firm had information spread across seven different systems. Consultants were spending an estimated 30-45 minutes per day searching for relevant project history, templates, and client records. New hires took months to become productive because institutional knowledge was trapped in silos.
Previous attempts to solve this — a company wiki, a shared drive reorganization — had failed because they required manual effort to maintain and quickly became outdated.
Our Approach
We designed a retrieval-augmented generation (RAG) system that connects to the firm's existing data sources without requiring migration or restructuring:
1. Multi-source ingestion. We built connectors to their email system, document management platform, project database, and internal wiki — indexing content in real time as it is created and updated.
2. Intelligent retrieval. Using vector search combined with metadata filtering, the system understands context — returning not just keyword matches but semantically relevant results ranked by recency, project relevance, and source authority.
3. Conversational interface. Consultants interact with the system through a chat interface embedded in their daily workflow tools. They ask questions in natural language and receive sourced answers with links to the original documents.
The Results
After a six-week pilot with 25 users:
65% faster access to relevant information — measured by time-to-answer for common research queries.
90% pilot user confidence — users rated the system as reliable and accurate in post-pilot surveys.
Reduced onboarding friction — new hires reported feeling productive weeks earlier because they could access institutional knowledge immediately.
Key Takeaway
The critical design decision was not to build a new knowledge base, but to meet the information where it already lives. By connecting to existing systems rather than requiring content migration, we eliminated the maintenance burden that killed previous solutions. The AI layer adds intelligence on top of infrastructure that already exists.