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    AI Automation
    Professional Services
    3 months from initial scoping to firm-wide rollout

    Internal Knowledge Search for a Professional Services Firm

    200-person consulting firm with 15 years of project documentation spanning thousands of proposals, deliverables, and internal memos across multiple practice areas.

    The Challenge

    Consultants spent hours searching shared drives and legacy project folders to find relevant past work. File naming conventions were inconsistent, and folder structures varied by practice area.

    Institutional knowledge was locked in documents that only original authors knew existed. Senior staff frequently answered the same questions from junior team members.

    New consultants took months to become productive because they could not easily find examples of past work relevant to their current projects.

    Our Approach

    We inventoried all documentation repositories including network shares, SharePoint sites, and legacy archives. The corpus totaled over 100,000 documents.

    We built an indexing pipeline that processes documents into searchable embeddings. All processing runs on the firm's own infrastructure with no data sent to external services.

    The search interface uses semantic matching so queries like 'client onboarding for financial services' return relevant results even without exact keyword matches.

    Each search result includes citation links back to source documents. Users can trace any answer to its original context.

    We implemented access controls that respect existing document permissions. Consultants only see results from documents they are authorized to access.

    Knowledge Search Architecture

    1

    Document Sources

    Network shares, SharePoint, and legacy archives are connected to the indexing system

    2

    Processing Pipeline

    Documents are parsed, chunked, and converted to searchable embeddings

    3

    Private Vector Database

    Embeddings are stored securely within the firm's infrastructure

    4

    Search Interface

    Consultants submit natural language queries through a web interface

    5

    Semantic Matching

    Queries are matched against document embeddings to find relevant content

    6

    Results with Citations

    Relevant excerpts are returned with links to source documents

    Results

    Average search-to-answer time dropped from 45 minutes to under 5 minutes
    New consultant onboarding accelerated with self-service access to past project examples
    Senior staff report fewer interruptions for routine knowledge questions
    Zero documents sent to external services, maintaining client confidentiality

    Facing a Similar Challenge?

    We would like to understand your situation and explore how we can help. No sales pressure, just a conversation about what is possible.