Product suite

Everything to govern AI from deploy to runtime

Six integrated products — two team portals, an AI assessment engine, and controls at every stage.

Self-hosted SaaS · Engineering + GRC · Deploy to runtime

How products connect

Gate Deploy Gate blocks ungoverned releases
Assess Regal AI produces assessment package
Prove Compliance Evidence & GRC audit
Enforce Runtime Enforcer on live agents

Product details

Our superpower

Regal AI

For Governance, Risk & Compliance teams

Turns every governance intake into a complete assessment package — risk tier, controls, assigned tests, and draft runtime policy — in minutes instead of weeks.

Risk tieringClassify exposure from intake data and use-case context
Control mappingRecommended controls aligned to regulation and policy
Compliance testsRequired and optional tests on conditional approval
Draft runtime policyAllowed and prohibited tools before go-live

Engineering Portal

For Software Engineering teams

Engineering Portal interface showing deploy gate, compliance evidence, and runtime monitor

Purpose-built workspace for teams shipping AI — from first deploy request through runtime monitoring, without leaving the engineering workflow.

Project dashboardGovernance status, tools, and policy version at a glance
Governance intakeTools, models, use case, and explicit non-goals
Deploy authorizationLive deploys tied to an approved policy token
Runtime monitorAgent event stream with allow/deny decisions

AI Governance Console

For Governance, Risk & Compliance teams

AI Governance Console interface showing request queue, Regal AI assessment, and policy alerts

Review, approve, audit, and respond — with Regal AI doing the heavy lifting on structured risk assessment.

Request queueDeployment requests with risk tier and status
Assessment reviewEvaluate Regal AI package; approve or request changes
Audit & authorizationSign off on evidence and authorize deploy
Policy alertsReal-time violation notifications post-deploy

Deploy Gate

Gate stage · Engineering & GRC

Stops ungoverned AI from reaching staging or production. When engineering triggers a deploy, the gate checks governance status and routes incomplete requests to GRC.

Environment coverageDev, test, and production deploy paths
Automatic GRC notifyNo manual email chains to start review
Clear block reasonsEngineers see exactly what intake is missing
Shadow AI preventionPolicy embedded in the delivery pipeline

Compliance Evidence

Prove stage · Engineering submits, GRC audits

Assigns compliance tests after conditional approval. Engineering submits results; Regal AI checks completeness before GRC audit authorization.

PII redaction testsVerify sensitive patterns masked before model calls
Prompt injection suitesAdversarial prompt testing with pass thresholds
Tool allowlist validationConfirm agents cannot call undeclared tools
Audit artifactsStored evidence chain for regulators and internal audit

Runtime Enforcer

Enforce stage · Both portals notified

Policy follows agents into production. Every tool invocation is evaluated against the approved manifest — allowed actions proceed; undeclared tools are denied and logged.

Allow / deny decisionsReal-time evaluation on every agent action
Policy tokensDeploy bound to a specific policy version
Violation alertsGRC and engineering notified on breaches
Full audit trailFrom deploy request through runtime events

End-to-end workflow

  1. Deploy gate Deploy Gate blocks release; GRC notified via Governance Console
  2. Intake & assess Engineering Portal intake → Regal AI assessment → conditional approval
  3. Evidence & audit Compliance Evidence submitted; GRC authorizes in Governance Console
  4. Authorized deploy Engineering Portal deploy with active policy token
  5. Runtime enforce Runtime Enforcer evaluates tool calls; violations logged and alerted

Walk through in the interactive demo →

See the product suite in action

Self-hosted SaaS on your infrastructure. Try the demo or request a walkthrough.