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Infrastructure Study

Stop Paying a Stranger by the Page to Read Your Own Files

Organizations that depend on document confidentiality, law firms, clinical practices, engineering groups, defense contractors, pay twice when they use a hosted search service: once per query and once in control they cannot get back. A properly built local index narrows millions of documents to the handful that matter, runs the model on hardware in the building, and returns a cited answer in seconds without an upload, a vendor copy, or a meter.

10 min read/9 cited sources
Questions

Frequently asked questions.

How is this different from uploading our files to a commercial AI tool?

The documents never leave your control. The index, the model, and the search all run on hardware sitting in your office or your data center. There is no upload step, no third-party copy of your archive, and no metered fee that grows every time someone runs a query.

Can a local system really handle millions of documents?

Yes. Retrieval across a very large archive is an indexing problem, not a model-size problem. A properly built local index narrows millions of documents to the handful that are actually relevant, and only those pass through the model.

What happens when the system is not sure about an answer?

It cites or it declines. Every answer is returned with the source document and the passage it came from, so a human can verify in seconds. When the retrieved material does not support an answer, the system says so rather than filling the gap.

Do we have to reorganize our files first?

No. Most archives we work with are a mess, and that is normal. Scanned PDFs, inconsistent naming, twenty years of folders nobody has touched. The ingestion layer handles the mess.

Sources

References and further reading.

  1. 01ABA, First ABA ethics guidance on generative AI tools (Formal Opinion 512)
  2. 02Lewis et al., Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (arXiv:2005.11401)
  3. 03Morris et al., Text Embeddings Reveal (Almost) As Much As Text (arXiv:2310.06816)
  4. 04NIST, AI Risk Management Framework 1.0
  5. 05NIST AI 600-1, Generative AI Profile
  6. 06NIST SP 800-171 Rev. 3, Protecting Controlled Unclassified Information
  7. 07Microsoft, Azure AI Document Intelligence pricing (per-page billing)
  8. 08Google Cloud, Document AI pricing (per-page billing)
  9. 09OWASP, Top 10 for Large Language Model Applications

This study is provided for general information and does not constitute legal advice. Consult qualified counsel about your specific circumstances.

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