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ARCHIVER

Contextual Document Storage & Discovery

Store, index, and enrich your documents with metadata and embeddings making them searchable, retrievable, and ready for AI-powered insights.

Overview

The Archiver node lets you store documents, packages, and cases alongside their metadata and vector embeddings, creating a fully searchable and context-rich layer. Whether your data must remain in a specific location or across multiple repositories, Archiver keeps metadata and embeddings in sync for fast retrieval, analytics, and AI-assisted workflows. Integrated with major providers and fully API-accessible, it enables conversational AI search, automated workflow integration, and advanced analytics on your documents ecosystem.

Capabilities

  • Indexed Storage

    Store documents with metadata and vector embeddings for fast lookup and AI-powered search.

  • Flexible Data Location

    Keep files wherever they are on-premises, cloud, or hybrid, while maintaining a synchronized contextual layer.

  • Flow Integration

    Pull documents, cases, or packages via Agent tools, extracted values, or QR codes to use in new workflows.

  • Taxonomy Management

    Maintain hierarchical document classifications and ensure structured organization.

  • Continuous Enrichment

    Run advanced models in the background to enhance embeddings, metadata, and federated context for each document.

  • Provider Integration

    Works out-of-the-box with Google Drive, SharePoint, OpenText, FileNet, and other major repositories.

Benefits

  1. Instant Discovery

    Search across documents and cases with AI-assisted conversational queries.

  2. Seamless Integration

    Incorporate documents into any workflow or downstream process.

  3. Conversational & Analytics Ready

    Make your documents discoverable and retrievable via chat or programmatic APIs. Ask business questions directly over your documents, e.g., 'How many loans were issued in this state?'

  4. Flexible & Secure Storage

    Keep documents in their original location while maintaining enriched contextual data.

FAQ

Yes. Archiver keeps metadata and embeddings synchronized regardless of where the documents reside.

Absolutely. All documents are indexed and embedded for fast retrieval via conversational AI or API queries.

Yes. Documents, packages, and cases can be pulled dynamically via Agent tools, QR codes, or extracted values.

Yes. Ask questions about your documents, generate metrics, and create actionable insights across your repository.