Deterministic AI powered by hierarchical knowledge graphs. No hallucinations — structured reasoning over your enterprise data.
Similarity search on isolated text chunks loses relationships, produces hallucinations, and wastes tokens. There's a better way.
Every component is designed for auditability, precision, and regulatory compliance.
4-level hierarchy: Knowledge Systems, Domains, Concepts, and Facts — mirroring how experts actually organize knowledge.
No hallucinations. The cognitive engine reasons over explicit graph structure, not probability distributions.
Five specialized retrievers — Graph, Vector, Community, Hierarchical, and Curated — work together for maximum precision.
Every answer traces back to specific graph nodes. Source indicators show exactly which retriever contributed each piece of context.
Built for regulated industries. Compliance-first design with governance controls, bias detection, and model validation.
Graph traversal retrieves only what's relevant — dramatically reducing token usage while improving answer quality.
Knowledge organized the way domain experts think — from broad systems down to atomic facts.
Watch how a query traverses the knowledge graph, gathers connected context, and generates a grounded response.
Where accuracy isn't optional and every decision must be traceable.
Validate statistical models, trace estimator relationships, and automate SR 11-7 compliance checks with graph-grounded reasoning.
Map regulatory requirements to model inventories. Ensure every AI system meets compliance standards with auditable knowledge paths.
Detect and explain bias in models using structured knowledge about fairness metrics, protected groups, and mitigation strategies.
Let's discuss how Graphenda can bring deterministic, auditable intelligence to your organization.