Platform
Fifteen modules,
one graph underneath
Every module is licensed on its own, so you can start with the single problem you have this quarter. What makes them a platform rather than a bundle is the shared Context Graph beneath them — each surface you add contributes entities and relationships that make every other module sharper.
Discover
Before you can govern AI, something has to count it. These modules build the register.
Shadow AI
Find every unsanctioned AI tool in use, score it by vendor and data risk, and coach people toward the sanctioned alternative rather than driving them to personal devices.
AI-BOM & Inventory
A live bill of materials for every agent, model, tool, MCP server, datastore and non-human identity across the estate.
Context Graph
Every entity and relationship in one graph, with computed attack paths, toxic combinations and reachability-based prioritisation.
Protect
Controls that act on the request rather than reporting on it afterwards.
AI Gateway
One inline control point for all AI traffic. Guardrails, PII redaction, per-key budgets and rate limits across every model provider.
Guardrails & Policy
Prompt injection, jailbreak and data-exfiltration controls written once as policy and enforced consistently on every surface.
Data Security
Validated PII, PCI and PHI detection, data lineage through agents and RAG, and native Microsoft Purview integration.
Detect & Respond
The agentic half. Agents sense, triage, investigate and respond — inside gates you set.
Agentic AI-SOC
A triage agent, an investigation agent and a response agent running the loop, inside an autonomy policy that decides what may act without asking.
Detection Fabric
One asynchronous scoring substrate under every surface — stream, behavioural, graph and media tiers, correlated into incidents.
Agentic Response
Response as composable agentic skills. Run a known workflow, or let the agent compose one for a threat nobody anticipated.
Test & Verify
Break it yourself, measure it honestly, and verify that what arrives is genuine.
Red Teaming
Automated adversarial testing on a schedule and in CI, with LLM-as-judge scoring and SARIF findings that gate the build.
Evaluations
Compare models on quality, safety and cost, and regression-test agent behaviour before it reaches production.
Deepfake Detection
Deepfakes across image, audio and video. C2PA and EXIF provenance resolve what they can deterministically; a calibrated ensemble handles the rest, and says when it is unsure.
Govern
The evidence layer — for the auditor, the board and the finance team.
Compliance
Continuous control mapping and audit-ready evidence for the EU AI Act, NIST AI RMF, ISO 42001, HIPAA, GDPR and SOC 2.
Observability
OpenTelemetry-native tracing for every agent run, tool call and model round-trip, with latency and token detail underneath.
FinOps
Token-level cost attribution by model, agent, team and user, with budgets and alerts that fire before the invoice does.
Start with one. Add the rest when they earn it.
Most pilots begin with the surface that worries the customer most and one module to govern it. The graph gets more useful with each addition, and nothing needs migrating when you expand.