Graph as the Control Plane
We build the platform that makes knowledge graphs both the memory and the control surface for autonomous AI systems. Node resolution as the operational primitive.
Making AI decisions auditable
Node Resolution
Resolve a node → the platform restricts what can be extracted, synthesizes how to search, selects which agents to run, and evaluates each candidate with evidence-weighted metrics.
Atomic Telemetry
Every node and edge carries metrics for traceability, explainability, confidence, cost, and latency — enabling comparable, auditable decisions across the entire graph.
Deterministic Outcomes
Results surface as ACCEPT / DEFER / REJECT with reasons and reproducible traces. Same inputs always produce the same outcome through idempotent execution.
Built for controlled autonomy
Our platform manages and coordinates language models, reasoning engines, extractors, and acquisition tools — all governed by the graph.
Agent Control & Policy
Built-in registry, routing, budgets, and safeguards for AI agents operating within defined boundaries.
Graph Orchestrator
Plans over context subgraphs instead of linear chains, enabling non-linear investigative workflows.
Metricized Explainability
Every change to knowledge is measurable at the smallest grain, so hallucinations are controlled and decisions are auditable.
Security & Governance
RBAC/ABAC, WORM audit, provenance hashes, data-residency controls, sandboxed execution, and PII redaction.
Border Control
Joint validation with Napier University supported by Interface Scotland
Business Intelligence
Commercial pilots and paying customers
Healthcare Digital Twins
Research in progress and working groups forming
Controlled autonomy for mission-critical AI
Hallucinations & Entropy
Local-scope extraction, strict type gating, and mandatory NER/ER checks prevent AI fabrication and ensure data quality.
Explainability & Traceability
Every decision links to an explanation subgraph. Every fact carries full, signed provenance for regulatory compliance.
Metrication of Autonomy
Hard/soft KPIs for agents and orchestration enable fair comparison and policy tuning across quality-latency-cost trade-offs.
Agent Coherence
Deterministic decisions, conflict arbitration, and budgeted parallelism keep multi-agent behavior aligned in non-linear work.
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