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DataVault turns scanned archives, emails, contracts, and correspondence into a searchable knowledge base, with auto-classification, full-text search, and an AI that answers with sources.
"... Solar Alpha GmbH engages the firm Meier & Söhne to perform the maintenance of Solar Park Alpha under Appendix 2, for the period Apr 1, 2023 to Mar 31, 2028. Compensation amounts to ..."
The maintenance contract runs until March 31, 2028. Contractor: Meier & Söhne.
Source: #3, Page 4
Every law firm, every construction department, every accounting team knows the scene. The document is somewhere. Just not where you're looking.
PDFs, EMLs, DOCX, scans, filed in folders, named by convention and chance. Full text doesn't exist. Context even less so.
Windows Search doesn't know OCR. Classic DMS search doesn't know semantics. 'Invoice Müller 2021' finds three documents. Or three hundred.
The colleague who manages client Müller knows where the master agreement is. When she's on vacation, nobody knows.
GoBD, HGB (German Commercial Code), GDPR. Provably immutable, findable for 10 years, tenant-separated. Classic file shares meet none of the three.
Three steps from raw folder chaos to a searchable company memory. No migration, no consultant project.
Drag-and-drop upload, email ingestion via a dedicated inbox, connections to common document stores. Supported: PDF, Office documents (text, spreadsheets, presentations), emails (EML/MSG), email archives (PST), images and scans.
Automatic text recognition (OCR). An AI classifies the document and extracts people, organizations, amounts, dates, and reference numbers.
Hybrid search combining full text and vectors. The AI answers questions with a citation, page reference, and traceable source.
Built on AWS in the EU, GoBD-oriented, multi-tenant from the very first user. Not a checklist of features, but the building blocks that actually carry the product.
10 years of immutability via S3 Object Lock. Every intake is logged tamper-evidently: a seamless, verifiable audit chain.
Every query runs in a tenant context. Even the database owner is bound by the policies. Cross-tenant leaks are no longer just a configuration error away.
The AI categorizes every document: invoice, contract, letter, court filing, report. Structured output with a strict JSON schema instead of free-text guessing.
People, companies, projects, amounts, reference numbers, dates, merged per tenant, without duplicates.
Semantic and exact full-text search work together. So you also find what's phrased differently.
The AI formulates the answer, with page number, source reference, and confidence. No claim without a documented finding.
Originals are stored KMS-encrypted in S3, previews separately and reproducibly. Deletion is blocked wherever retention applies.
DataVault isn't built for consumer applications. It's for organizations with 50 to 1,000 employees, where every question has a source and every answer has a consequence. Six example scenarios:
Results classified as invoices, with extracted amounts, IBAN, and invoice numbers. Every match with a page citation into the original.
All documents with this case reference, sorted chronologically. Case references are automatically recognized and extracted during intake.
The AI answer names the firms from the contract headers, with citation and page reference from master agreements and offers.
Results filtered by document type contract, with term dates extracted from the contract text.
Full-text and semantic matches across drawing headers and approval emails, sorted by date, with a click into the source document.
All documents with this claim number: assessments, attorney letters, emails. Chronological, every answer with a source link.
A 30-minute demo with your real sample documents. If DataVault doesn't answer your questions, the demo was free. If it does, you'll know why.