Tech Stack · Explorer

Ask anything.
Get cited evidence.

Not a chatbot.
A 3-agent intelligence swarm grounded in your organizational graph. Every answer is cited.
Every citation links to a specific graph node.
If the answer isn't in the graph, the Explorer doesn't invent it.

The 3-Agent Swarm

Three agents. One truth.

🛡️

Gatekeeper

· Plans the query

Determines what concepts are relevant, what graph traversal is needed, and what level of the ontology to explore. Prevents off-target searches.

🔍

Searcher

· Retrieves evidence

Executes multi-hop graph traversals. Retrieves relevant nodes, assets, confidence scores, and relationship paths from the knowledge graph.

⚡

Synthesizer

· Generates cited output

Produces the final answer, citing every graph node it used. Each statement is traceable to a specific concept, asset, or relationship in the organizational graph.

Example Queries

Questions you can now answer.

"How does our KYC process work?"

Cited answer with service dependencies, API endpoints, and compliance links.

"What breaks if we change this compliance rule?"

Full impact cascade across concepts, services, and code.

"Why does finance say X and product say Y?"

Single enforced definition surfaced from the ontology.

"Prove our loan approval process is compliant"

Lineage trace from regulation to source code in seconds.

"Which teams are affected by GDPR Article 17?"

Cross-domain traversal through organizational graph.

OAG, Not RAG

Ontology-Augmented Generation.

RAG feeds text chunks to LLMs.
Ambiguity in, hallucination out.
OAG feeds typed graph objects with relationships.
The AI's output is structurally constrained by the ontology.

Cost per query: $0.01–$0.05 (Claude Sonnet routing) · Per-concept governance clearance on every node

Tech Stack · Explorer

Query the graph.

Ask any question about the enterprise. Get cited answers with full lineage. See it running on a live banking domain.

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