Your institutional knowledge isn't just data—it's a living network of expertise, relationships, and context. We help you curate, codify, and connect this knowledge into intelligent graphs that agents can understand and navigate.

Stop treating knowledge as isolated documents. Build graph-structured intelligence that captures how ideas relate, evolve, and interconnect—creating the contextual foundation for truly agentic AI systems.

Our Services

Knowledge Curation & Codification

Transform scattered tribal knowledge into structured, taxonomized, graph-connected intelligence. We help you capture implicit expertise, build relationship metadata, and create category hierarchies that reflect how your organization actually thinks.

Graph RAG Systems

Build multi-hop knowledge graphs with semantic embeddings, centrality scoring, and relationship traversal. Our graph RAG combines vector search with explicit human-curated connections for context-aware retrieval that understands how concepts relate.

Knowledge Operations (KnowOps)

Monitor knowledge health and freshness over time. We provide automated staleness detection, usage analytics, change impact analysis, and alerts when critical knowledge needs attention—keeping your graph current and actionable.

Why Graph-Based Knowledge Curation?

Capture Relationships, Not Just Documents

Knowledge isn't linear. Graph structures preserve how concepts relate—prerequisites, alternatives, contradictions, and extensions. Agents navigate this web of meaning, not just keyword matches.

Human-Curated Context

Taxonomy, categories, and explicit "related docs" metadata beat pure vector similarity. We help you codify institutional wisdom so agents inherit your organization's understanding of what's important.

Multi-Scope Collections

Separate private research from org-wide knowledge bases. Category-filtered retrieval ensures agents access the right scope—personal notes, team wikis, or company-wide policies.

Centrality & Importance Scoring

Not all documents are equal. Our graph algorithms compute centrality based on bidirectional relationships, surfacing hub documents that are foundational to your knowledge ecosystem.

Always Evolving

Knowledge graphs aren't static. As you curate new connections, update categories, or refine relationships, the entire system's understanding adapts—no retraining required.

Query-Ready Structure

Category-filtered search, relationship-aware retrieval, and metadata-rich context make your knowledge graph instantly queryable by humans and AI systems alike.

How Knowledge Curation Works

1

Audit & Taxonomy Design

We map your existing knowledge landscape—documents, wikis, databases, tribal knowledge. Then we co-design a taxonomy that reflects how your organization categorizes expertise.

Category hierarchies, tag vocabularies, relationship types
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2

Curation & Codification

Human-in-the-loop knowledge structuring. We help you curate explicit relationships, assign categories, and tag content with metadata that captures organizational context.

Related-doc linking, category assignment, metadata enrichment
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3

Graph Indexing & Embedding

Content is chunked, embedded into vector space, and indexed into scoped collections (user vs org). Graph metadata (centrality, relationships, categories) is stored alongside embeddings.

ChromaDB collections, bidirectional centrality, multi-hop graphs
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4

Ongoing Operations & Monitoring

Set up automated freshness checks, usage analytics, and staleness alerts. Monitor knowledge health, track changes, and identify gaps before they become problems.

Staleness detection, impact analysis, usage dashboards, health alerts

Knowledge Graph Use Cases

Research OS for Teams

Enable research teams to curate findings, link related studies, and build evolving knowledge graphs. Track citation patterns, identify knowledge gaps, and monitor when key research needs updating.

Internal Knowledge Wikis

Transform company wikis from flat hierarchies into graph-structured intelligence. Category-based organization (HR, Engineering, Legal) with explicit relationships helps employees find contextual answers fast.

Compliance & Policy Management

Build regulatory knowledge graphs with explicit policy → procedure → audit trail relationships. Track which policies supersede others, monitor freshness, and get alerts when regulations change.

Technical Documentation Systems

Curate API docs, tutorials, and troubleshooting guides with prerequisite relationships. Surface centrality-ranked hub documents and detect when critical pages haven't been updated recently.

Product Strategy Knowledge Bases

Link customer insights, competitive research, and product decisions into a decision graph. Trace "why we built this" by following reasoning chains and track which insights influenced which decisions.

Customer Success Knowledge Graphs

Curate support articles with category tags (Billing, Integrations, Troubleshooting). Monitor article usage, detect stale content, and surface high-impact documents based on centrality scoring.

Our Knowledge Technology Stack

Knowledge Graphs

  • MongoDB (nodes + relationships)
  • Graph traversal algorithms
  • Centrality computation
  • Taxonomy hierarchies

Vector Embeddings

  • ChromaDB (scoped collections)
  • Sentence transformers
  • Metadata-aware search
  • Hybrid scoring (vector + graph)

Curation Tools

  • Visual graph editors
  • Category management
  • Related-doc pickers
  • Tag autocomplete

Operations & Monitoring

  • Staleness detection algorithms
  • Change impact tracking
  • Usage analytics dashboards
  • Automated health alerts

Ready to build intelligent knowledge graphs?

Let's transform your institutional knowledge into structured, queryable, and maintainable context systems.

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