Knowledge Graph for Agentsv1.0.0

A sales team uses a knowledge graph to answer multi-hop queries like 'who at Acme Corp works with Alice?' or 'which accounts use our product and have a referral from Bob?'. This enables account mapping and warm introductions that flat search cannot provide.

An IT operations agent uses a graph to traverse dependencies between servers, databases, and microservices. For example, 'what services are on the production server?' or 'which applications depend on PostgreSQL?'. This aids in outage impact analysis and change management.

A research assistant extracts entities (authors, institutions, methods) from papers and creates co-occurrence edges. Queries like 'which papers use Graph Neural Networks and cite work by Jane Smith?' yield multi-hop results, enabling literature review acceleration.

A legal AI ingests contracts and case law, extracting parties, jurisdictions, and clauses. Users ask 'which contracts involve Acme Corp and mention force majeure?' or 'which cases reference this precedent?'. Graph traversal finds connections missed by keyword search.

A recruiting agent builds a graph of candidates, companies, and skills from resumes and job postings. Queries like 'who worked at Google as a data scientist and knows Kubernetes?' return candidates via skill/company edges, improving matching accuracy.

Offer the knowledge graph layer as a premium feature on top of existing search or agent platforms. Charge per query or per node, with pricing tiers based on graph size and traversal depth.

Provide professional services to build and tune the graph layer for enterprise clients, including entity extraction pipelines, ontology design, and hybrid search integration. Recurring maintenance contracts follow.

Expose the graph querying capability as a REST API (e.g., 'GET /graph/traverse?entity=Alice&hops=2'). Charge per API call or via monthly subscription with rate limits. Ideal for developers embedding graph reasoning into their own agents.