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InfoLibrarian Knowledge Graph Engine
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What InfoLibrarian Knowledge Graph Engine is
InfoLibrarian Knowledge Graph Engine converts enterprise metadata into a governed knowledge graph for retrievable, traceable context. It ingests presentations, documents, PDFs, spreadsheets, diagrams and audio while preserving table relationships and diagram structure. Hashing, deduplication, near-duplicate detection, version and lineage tracking, and node provenance help maintain corpus history. Declarative mappings support CSV, Excel, JSON and XML, plus enterprise data models, catalogs, process models and organizational structures. Teams can define node types, relationship types and properties, constrain extraction to an ontology, or run schema-free. Retrieval combines vector and keyword search, reranking, entity expansion and graph traversal, with deterministic or hybrid modes. Asynchronous scoring measures faithfulness, relevancy, contextual precision and contextual recall, with subject-area benchmarks. Interfaces include a command line, programmable API, MCP server and interactive question-answering interface. The stack uses a native property graph database, local open-weight models through Ollama, and containerized self-hosting. It can run air-gapped or in the cloud, with processing inside a firewall.
Who it suits
It suits teams managing document sprawl that need governed context for agents or a data-product foundation. The maker recommends starting with one subject area rather than using it as a massive enterprise-wide operational decision platform.
What it does well
- Ingests documents, diagrams, audio and structured data
- Supports ontology modeling or schema-free extraction
- Combines vector, keyword and graph retrieval
- Scores answer quality with subject benchmarks
- Offers air-gapped and cloud deployment
What to know first
- Paid commercial license with pricing on request
- Ecosystem is described as small
- Not intended for massive enterprise-wide operational decisions
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| Platform IP license | Commercial license; runs in your environment or cloud; contact for licensing | On request |
As infolibcorp.com lists them, read 8 Oct 2026. The maker's own page has the final word.
Verdict
InfoLibrarian combines broad ingestion, governed ontology controls, graph retrieval and measurable answer evaluation. Its self-hosted and air-gapped options fit organizations that require internal data control, while buyers should assess the smaller ecosystem and stated scope limits.
Facts from InfoLibrarian Knowledge Graph Engine's own pages
- Commercial availability
- The engine is commercial intellectual property available by license, rather than a public self-serve product store. · infolibcorp.com, 8 Oct 2026
- Corpus hygiene
- Ingestion includes hashing, deduplication, near-duplicate detection, version and lineage tracking, and provenance for graph nodes. · infolibcorp.com, 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, 8 Oct 2026
- Document ingestion
- It reads presentations, documents, PDFs, spreadsheets, diagrams and audio, preserving table relationships and diagram structure. · infolibcorp.com, 8 Oct 2026
- Founded
- 2005 · infolibcorp.com, 28 Sept 2026
- Headquarters
- Sarasota, Florida, USA · infolibcorp.com, 28 Sept 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, 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, 8 Oct 2026
- Interfaces
- The engine provides a command line, programmable API, MCP server and interactive interface for question answering and inspection. · infolibcorp.com, 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, 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, 8 Oct 2026
- Measurement
- Answers are asynchronously scored for faithfulness, relevancy, contextual precision and contextual recall, with benchmarks per subject area. · infolibcorp.com, 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, 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, 8 Oct 2026
- Purpose
- The engine turns structured and unstructured enterprise metadata into a governed knowledge graph for retrievable, traceable, measurable context. · infolibcorp.com, 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, 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, 8 Oct 2026
Where InfoLibrarian Knowledge Graph Engine stands on Freedom251
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