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    AI Automation
    Professional Services
    A build like this typically runs for three months from discovery through rollout.

    REPRESENTATIVE BUILD

    Search Internal Knowledge Without Exposing Private Data

    Representative 200-person consulting firm scenario with 15 years of proposals, deliverables, and internal memos across several practice areas.

    The Challenge

    Consultants search shared drives and old project folders with inconsistent file names and folder structures.

    Useful knowledge remains inside documents that only their original authors know.

    New consultants need cited examples that match their current work and access rights.

    Our Approach

    A fixed-scope discovery inventories network shares, SharePoint sites, legacy archives, user roles, and high-value search tasks.

    A private index processes a corpus of more than 100,000 documents inside the approved infrastructure.

    Semantic search returns cited source passages while existing document permissions control each result.

    An evaluation suite tests retrieval quality, citation accuracy, permission boundaries, and abstention before go-live.

    Users flag weak results for review, and the client team approves corpus and prompt changes.

    The client owns the code, prompts, tests, and runbooks. The build has no seat-based price.

    Knowledge Search Architecture

    1

    Document Sources

    Network shares, SharePoint, and legacy archives connect to the index.

    2

    Processing Pipeline

    The pipeline parses, splits, and converts documents into searchable vectors.

    3

    Private Vector Database

    The approved infrastructure stores vectors and source links.

    4

    Search Interface

    Consultants submit natural language questions through a web interface.

    5

    Semantic Match

    The search layer finds relevant passages within each user's access rights.

    6

    Cited Results

    Each result links to its source document and context.

    What This System Changes

    Consultants start with cited passages instead of a blind folder search.
    Permission checks prevent the search layer from widening document access.
    Feedback queues give knowledge owners a clear human review path.
    Private deployment keeps client material outside public AI services.
    Buyers can use their own search volume and labor data in the ROI calculator.

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