AI agents extract entities, relationships, and temporal context from your unstructured data. The graph builds as new documents arrive. Query it in plain English. Live in 3 weeks.
Knowledge graphs fix that. Here are the numbers.
Natural language queries. Instant answers. Connections across siloed sources surfaced automatically. No manual cross-referencing.
People, organizations, locations, events, relationships - identified and extracted automatically. 90%+ accuracy out of the box.
Pilot data sources connected. Graph built. Value proven. 3 weeks. Then scale across the organization.
Extracts entities. Maps relationships. Tracks changes over time.
People, orgs, products, locations, dates, custom domain entities - pulled from emails, docs, chat logs, and reports. No manual tagging.
Who reports to whom. Which products belong to which categories. How projects connect to customers. Hidden connections surfaced automatically.
When did they join? When was that product discontinued? Query at any point in time. Track how entities and relationships changed.
Docs, databases, APIs, emails, Slack, Confluence, SharePoint. Entities merged across systems. Duplicates resolved. One unified knowledge layer.
"Who worked with Sarah on Phoenix last quarter?" Plain English in. Graph query executed. Connected entities retrieved. Answer with evidence and confidence score out.
New documents arrive. AI extracts entities. Relationships update. Outdated info deprecated. The graph evolves. No manual curation.
Production knowledge graphs across enterprise functions
Org charts that update themselves. Expertise tracked by what people actually work on, not their title. "Who knows Kubernetes networking?" answered in seconds.
Purchase history, interactions, support tickets, product usage, account team relationships - all connected. "Customers who bought X also had issues with Y." Surfaced automatically.
"Show all controls related to GDPR Article 32 and their current status." Requirements mapped to controls. Compliance status tracked over time. Full history.
APIs, services, databases, teams - relationships mapped. Dependencies understood. Impact analysis for changes done in seconds, not meetings.
Traditional knowledge graph projects take 6-12 months and require graph database specialists. Forward Deployed Engineers build production graphs in 4 weeks.
Typical enterprise deployment
Every document ingested makes the graph smarter. Every query makes it more useful. AI that gets better on Day 200.