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Claude & ChatGPT — Supercharged.
כל המסמכים · 300+ כלי AI · הגדרה ב-30 שניות
Claude· ChatGPT· Cursor· Gemini· +50
התחבר עכשיו
תמחור
AI-DMS

Features

Knowledge graph across all documents

Link documents via content and relationships — searchable for teams and agents.

Made for real business. Not for hype.

In the same account

More than extraction

  • Extract

    AI OCR with bounding boxes — 69 types, fields with location.

    from €9 per 1,000 pages

  • HITL review

    Seamless in the job path — task and document also on mobile.

    Web + Mobile

  • Sign

    SES signatures from the same credit balance.

    SES from the balance

  • WORM archive

    Audit-proof filing and audit trail.

    included

Pricing model with qualification tiers

Our prices are public — including partner terms. Transparent list price for partners and integrators.

Unit: Price per 1,000 pages

TierElite Partner (−70%)Partner (−40%)Enduser
Basic €9.00 €18.00 €30.00
Premium €12.00 €24.00 €40.00
Ultra €30.00 €60.00 €100.00

Billing is internal in credits; amounts follow the selected currency (base: list price).

Elite terms after qualification — criteria and program are public: Pricing · Partner program

מהימן על ידי חברות מובילות ברחבי העולם

Relationships between documents

Extracted entities create links — useful for cases, contracts and document chains.

Search by content instead of folders

Instead of deep folder trees, teams find documents via fields, types and relationships.

Agent access via MCP

AI agents can query the graph via MCP tools — in the same account as the archive.

FAQ

What is a knowledge graph over documents?

A connected view of entities, relationships and records — not only folders and file names.

What questions can be asked?

Relationships, deadlines, amounts and cross-workspace context — via UI, API or MCP.

Is manual tagging required?

Many links come from extraction and classification; manual curation remains optional.

Is the graph API-capable?

Yes — queries and updates via REST/MCP.

How does this relate to IDP?

Extracted fields feed the graph; the graph makes fields usable across documents.

What does Knowledge Graph cost?

Usage-based via credits/plans.

Where are embeddings processed?

In PaperOffice EU infrastructure.

Who is it for?

For teams that need knowledge from records, not only file storage.