InfoLibrarian Knowledge Graph Engine
The facts below are what the maker publishes about InfoLibrarian Knowledge Graph Engine, checked and dated. Our editors have not written about it yet.
Plans and prices
From InfoLibrarian Knowledge Graph Engine's own pricing page, checked 8 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Platform IP license | Priced on request | Commercial license; runs in your environment or cloud; contact for licensing |
The facts
Each one read from InfoLibrarian Knowledge Graph Engine's own pages, with the date it was checked.
What it does
- Commercial availability
- The engine is commercial intellectual property available by license, rather than a public self-serve product store.checked 8 Oct 2026
- Corpus hygiene
- Ingestion includes hashing, deduplication, near-duplicate detection, version and lineage tracking, and provenance for graph nodes.checked 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.checked 8 Oct 2026
- Document ingestion
- It reads presentations, documents, PDFs, spreadsheets, diagrams and audio, preserving table relationships and diagram structure.checked 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.checked 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.checked 8 Oct 2026
- Interfaces
- The engine provides a command line, programmable API, MCP server and interactive interface for question answering and inspection.checked 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.checked 8 Oct 2026
- Measurement
- Answers are asynchronously scored for faithfulness, relevancy, contextual precision and contextual recall, with benchmarks per subject area.checked 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.checked 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.checked 8 Oct 2026
- Purpose
- The engine turns structured and unstructured enterprise metadata into a governed knowledge graph for retrievable, traceable, measurable context.checked 8 Oct 2026
- Retrieval
- Retrieval offers hybrid vector and keyword search, reranking, entity expansion, graph traversal and an explicit deterministic or hybrid mode.checked 8 Oct 2026
- Structured sources
- Declarative mappings support CSV, Excel, JSON and XML, alongside enterprise data models, catalogs, process models and organizational structures.checked 8 Oct 2026
The company
- Founded
- 2005checked 28 Sep 2026
- Headquarters
- Sarasota, Florida, USAchecked 28 Sep 2026
- Maker and location
- The company describes InfoLibrarian as Brian Brewer’s company and portfolio; its license announcement is datelined Sarasota, Florida.checked 8 Oct 2026
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