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UMAI Platform
Customer-hosted AI governance and guardrail platform for apps, agents, and browser AI usage.
Platform overview
One control plane for governed AI.
UMAI is the umbrella platform for guardrail design, runtime enforcement, testing and evaluation, monitoring and audit, and browser-based AI governance. It connects policy authoring, runtime control, and evidence generation inside one enterprise operating layer.
The platform brings these surfaces into one operating model so design, enforcement, evaluation, and evidence stay connected.
UMAI Control Center
Guardrail design, policy management, and release workflows.
Testing & Evaluation
Datasets, simulations, and validation runs before rollout.
Monitoring & Audit
Operational alerts, policy outcomes, and review context.
Browser Governance
Govern ChatGPT, Gemini, and Claude usage in managed browsers.
UMAI Control Center
Design, version, and publish guardrails from one control layer.
The Control Center is where teams build policies, manage guardrails, publish approved versions, and separate projects and environments without fragmenting governance operations.
Testing & Evaluation
Validate policies before they become production assumptions.
Run datasets, simulations, red-team style checks, and performance validation so teams can measure guardrail behavior before live rollout and keep tuning it after deployment.
Core platform modules
The main platform components.
UMAI Platform is the parent product story. Each module handles a different part of governed AI deployment, then works together as one system.
UMAI Control Center
Build policies, manage guardrails, publish versions, and control projects and environments from one operational surface.
Testing & Evaluation
Run datasets, simulations, red-team style checks, and performance validation before policies hit live traffic.
Monitoring & Audit Ledger
Track alerts, decisions, approval workflows, tamper-evident records, and evidence packs across governed AI operations.
Browser Extension
Govern ChatGPT, Gemini, and Claude usage directly in the browser without rewriting the target AI applications.
How the platform works
One governed workflow from policy design to evidence.
The platform keeps policy, enforcement, evaluation, and evidence connected instead of scattering them across separate tools.
Step 01
Design policies
Define the guardrails, approval rules, and governance thresholds that matter for your environment.
Step 02
Publish guardrails
Version and release approved policy packs into the right projects, teams, and environments.
Step 03
Enforce everywhere
Apply controls across AI apps, agents, APIs, and browser AI usage from one platform layer.
Step 04
Monitor and prove
Track outcomes, run evaluations, and export evidence for security, audit, and compliance review.
Key capabilities
Platform capabilities
UMAI keeps the platform surface concise, but covers the policy, workflow, telemetry, and evidence depth enterprise AI teams need to deploy governed systems cleanly.
Policy builder
Guardrail templates
AI-assisted generation
Versioning and publishing
Alerting
Evidence packs
Approval workflows
API-based enforcement
Browser telemetry
Evaluation datasets
Architecture and deployment
Built for customer-hosted enterprise infrastructure.
UMAI is designed to fit controlled environments, not force enterprise programs into a tooling model that breaks governance or security requirements.
Customer-hosted deployment
On-prem or controlled environment support
Internal registry support
LDAP-backed access
OpenAI-compatible inference support
Enterprise infrastructure compatibility
Security & Compliance
Enterprise readiness comes from traceable controls, clear review paths, and evidence that stays tied to actual runtime behavior.
- Tamper-evident audit ledger for governed AI decisions
- Evidence packs for internal and external review
- Governance workflows with approval and review paths
- Traceability across prompts, outputs, tool actions, and operator events
Integrations & Implementation Paths
UMAI supports the implementation paths enterprises already use, then adds platform governance on top instead of forcing a new application architecture.
Final CTA
Bring governed AI deployment into one enterprise platform.
Use UMAI Platform as the parent operating layer for policy, runtime control, evaluation, monitoring, and evidence.