Enterprise AI gateway

One secure gateway for every AI model.

Control access, route workloads, protect sensitive data, and track AI spend across cloud and private models.

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Vendor-neutralHybrid deploymentAuditable by design
OpenGate Control Layer● Systems operational
▣Applications
⌘Developers
APIAI agents
AI Gateway
Access control
Smart routing
Policy enforcement
Usage telemetry
AICloud models
◇Private models
▦Local AI
Requests today42.8K
Policy coverage100%
Cost saved31%
The AI control gap

Enterprise AI is expanding faster than it can be controlled.

Every new model, tool, and team adds another integration, another bill, and another path for sensitive data to escape established controls.

01.

Scattered AI usage

Teams use disconnected AI tools, models, and APIs without a shared control layer.

02.

Uncontrolled costs

Token consumption grows across users and applications without central budgets, routing, or visibility.

03.

Sensitive-data exposure

Confidential information can enter external models without consistent safeguards or audit evidence.

How OpenGate works

One control layer across your entire AI stack.

Integrate once. Apply consistent policy, routing, cost controls, and observability to every approved AI request.

Applications & users
▣Applications
⌘Developers
APIAPIs
◎AI agents
◇
Access control
↔
Routing
✓
Policy
＄
Cost tracking
⌁
Monitoring
Approved AI
AIManaged providersOpenAI · Bedrock · Vertex AI
◇Private modelsYour own deployments
▦Local AIRunning on your hardware
☁Private cloudYour cloud tenancy

Every request is authenticated, checked against policy, routed to an approved model, measured, and recorded in one auditable workflow.

01 / CONNECT

Connect once

One standard interface for approved AI models across cloud, private, and local environments.

02 / OPTIMISE

Route intelligently

Balance cost, performance, risk, availability, and data-residency requirements.

03 / GOVERN

Control every request

Apply access policies, guardrails, logging, and audit controls consistently.

Product proof

See, control, and optimise every AI request.

Give platform, security, and finance teams one operational view without forcing business users to change how they work.

AI traffic overview

● Live monitoring
Requests42,892
Active models12
Blocked events187
Monthly spend$24.8K
Customer support assistantPrivate model
Engineering copilotCloud model
Contract reviewEU-hosted model
Built for your team

One platform. Four reasons to care.

Scale AI without multiplying infrastructure

Bring model access, governance, cost control, and deployment flexibility into one vendor-neutral layer.

  • Reduce duplicated integrations
  • Avoid model-provider lock-in
  • Standardise controls across teams
Deployment & trust

Deploy where your data needs to stay.

Support enterprise AI without forcing sensitive workloads outside approved infrastructure.

Central access policies
Encrypted connections
Request-level audit logs
Data-residency routing
Private-model support
Role-based controls
☁

Managed cloud

Fast deployment for approved enterprise workloads.

◇

Customer VPC

Operate inside your controlled cloud environment.

▦

Private cloud

Connect internal models and protected data services.

⌂

On-premises

Maintain control for sovereign or restricted workloads.

Frequently asked questions

Technical clarity from the start.

Commercial APIs, private cloud endpoints, and models you host yourself, including on-premise. Because every request goes through one interface, adding or replacing a provider is a configuration change rather than an application rewrite.
That is yours to decide. Retention is set by policy for each deployment, and because the gateway runs inside your own environment, whatever you choose to keep stays on your infrastructure. It never reaches us.
Yes. Usage and spend are attributed to the user, team, application and use case behind each request, so AI can be charged back like any other shared service rather than arriving as one unexplained invoice.
Yes. Routing rules send a request to a specific model based on how sensitive the workload is, whether that model is approved for it, where the infrastructure sits, and any data residency requirement that applies.

Bring every AI workload under one governed control layer.

Book a technical demo →
Book a technical demo

See it run against your own policies.

One working session with your security and platform teams. We map your data classification to approved models, walk the deployment options, and show the audit record a real request leaves behind.

What you leave with

  • ✓
    Deployment modelCloud, your own tenancy, or fully on-premise.
  • ✓
    Your classification mapWhich models each tier is allowed to reach.
  • ✓
    A real audit exportPulled from a live request, not a prepared sample.
  • ✓
    A 30-day rollout planFour weeks, each with a named owner and an exit test.

Business contact details only — never sold, never passed on, no mailing list.

We reply within one business day.