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InfoLibrarian Knowledge Graph Engine

Sarasota, Florida, USA

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Platform IP license

Priced on request

Commercial license; runs in your environment or cloud; contact for licensing

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On the record

Commercial availability
The engine is commercial intellectual property available by license, rather than a public self-serve product store.infolibcorp.com · read 8 Oct 2026
Corpus hygiene
Ingestion includes hashing, deduplication, near-duplicate detection, version and lineage tracking, and provenance for graph nodes.infolibcorp.com · read 8 Oct 2026
Deployment and data control
The stack can run air-gapped or in the cloud; the maker says processing and inference can stay inside the firewall with no third-party model inference.infolibcorp.com · read 8 Oct 2026
Document ingestion
It reads presentations, documents, PDFs, spreadsheets, diagrams and audio, preserving table relationships and diagram structure.infolibcorp.com · read 8 Oct 2026
Integration options
The platform page names Anthropic, OpenAI, Hugging Face, Ollama, Azure OpenAI, private and on-prem endpoints, and other approved hosts as model options.infolibcorp.com · read 8 Oct 2026
Intended users
The maker describes the best fit as teams with accumulated document sprawl that need reliable agent context or a data-product foundation, starting with one subject area.infolibcorp.com · read 8 Oct 2026
Interfaces
The engine provides a command line, programmable API, MCP server and interactive interface for question answering and inspection.infolibcorp.com · read 8 Oct 2026
Limitations
The maker says it is not intended as a massive-scale enterprise-wide operational decision platform and describes its ecosystem as small and governance as fit for purpose rather than a formal operating model.infolibcorp.com · read 8 Oct 2026
Maker and location
The company describes InfoLibrarian as Brian Brewer’s company and portfolio; its license announcement is datelined Sarasota, Florida.infolibcorp.com · read 8 Oct 2026
Measurement
Answers are asynchronously scored for faithfulness, relevancy, contextual precision and contextual recall, with benchmarks per subject area.infolibcorp.com · read 8 Oct 2026
Models and infrastructure
It uses a native property graph database and local open-weight models served through Ollama, and is containerized and self-hostable without a managed-service dependency.infolibcorp.com · read 8 Oct 2026
Ontology
Users can define and extend node types, relationship types and properties, with extraction constrained to the governed ontology or run schema-free.infolibcorp.com · read 8 Oct 2026
Purpose
The engine turns structured and unstructured enterprise metadata into a governed knowledge graph for retrievable, traceable, measurable context.infolibcorp.com · read 8 Oct 2026
Retrieval
Retrieval offers hybrid vector and keyword search, reranking, entity expansion, graph traversal and an explicit deterministic or hybrid mode.infolibcorp.com · read 8 Oct 2026
Structured sources
Declarative mappings support CSV, Excel, JSON and XML, alongside enterprise data models, catalogs, process models and organizational structures.infolibcorp.com · read 8 Oct 2026

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