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
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
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
Graph Indexing & Embedding
Content is chunked, embedded into vector space, and indexed into scoped collections (user vs org). Graph metadata is stored alongside embeddings.
ChromaDB collections, bidirectional centrality, multi-hop graphs
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.
Internal Knowledge Wikis
Transform company wikis from flat hierarchies into graph-structured intelligence with explicit relationships.
Compliance & Policy Management
Build regulatory knowledge graphs with explicit policy → procedure → audit trail relationships.
Technical Documentation Systems
Curate API docs, tutorials, and troubleshooting guides with prerequisite relationships.
Product Strategy Knowledge Bases
Link customer insights, competitive research, and product decisions into a decision graph.
Customer Success Knowledge Graphs
Curate support articles with category tags and surface high-impact documents via 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.