AGate: Mission Control for Your Enterprise AI
Your teams already use AI. With AGate, you can govern all of it.
- SOC 2 Ready
- GDPR-Compliant
- EU AI Act Ready
80%
faster AI use-case implementation
5
months to a production AI platform
100%
data security and auditability
2,500+
people on one governed platform
Trusted by
Trusting Adastra’s AI expertise
What I value in Adastra’s team is the stakeholder alignment and cross-functional facilitation they brought alongside strong technical expertise. They read the room, bridge interests across teams, and get our departments speaking the same language.
overview
Enterprise AI Governance that Controls Access, Spend and Evidence Across Every Model
No shadow tools. No surprise invoices. Every AI request in your company goes through one governed endpoint you own, so you can see it, control it, and prove it.
The right models in the right hands
Marketing gets image models, developers get the coding model, everyone else gets the standard one. Bound to your identity groups, enforced on every request.
Overspend stops at the request
Limits per user, project and department block the call before the money is gone, instead of alerting you after.
The audit answer is already there
Every request logged with the person, project and model behind it, plus prompt bodies and an EU residency verdict per model.
Challenges
AI Is No Longer Just a Chat
AI now takes actions inside your systems. Teams use ChatGPT, Copilot, and Claude daily. Developers wire agents into SAP and your CRM. Without a governed layer, four risks compound fast.
Budgets alert. They do not block.
No native hard spend cap means the documented pattern is an alert, then a runbook. API gets shuts off after the money is already gone.
Shadow AI outruns approval
Unapproved tools spread faster than anyone can review them, and agents multiply on top. Nobody sees what is being sent, or what comes back.
Cloud access rules answer the wrong question
Cloud identity governs resources, not business groups. Getting to “marketing may use this, finance may not” means a separate deployment per group, or a policy layer you maintain forever.
No cloud reports beyond its own estate
Azure chargeback stops at Azure. AWS cost allocation runs on AWS tags. Neither answers the question a CFO or an auditor actually asks.
91%
of organisations hit sensitive-data leakage risk
Check Point, 2025
€5–20M
potential fine per incident (NIS2, EU AI Act)
per regulatory breach
30–50%
of GenAI time lost to compliance overhead
McKinsey, 2025
Solution
A closer look at the AGate platform
From the governed gateway to the sanctioned workspace, here is what each component does.
LLM Gateway
Gain control of the AI already happening.
- One API endpoint for all LLM providers
- Load balancing with automatic failover
- SSO authentication (Entra ID, Okta)
- Full audit trail: every request logged
- Spend tracking & budget limits per user / project / department
- Admin Portal + Grafana dashboards
Chat
Give employees a sanctioned AI tool so they stop using shadow ones.
- Governance only works if people prefer the governed path
- Self-hosted enterprise chat, data never leaves your tenant
- Multi-model: switch providers in one click
- AI agents with MCP tools (SharePoint, Jira, SAP)
- Custom agent builder, no coding needed
- Branded to look like your company’s tool
How agate works
One governed path from any app to any model
AGate deploys inside your own cloud tenant and becomes the single governed path between every application and every model: identity, routing, spend, and audit enforced on each request.
Consumers
Control plane
LLM providers
- Runs in your tenant
- One governed egress
- Every request logged
Your cloud stays. Keep your existing models, regions, and tooling. AGate layers governance on top, with no migration.
Outcomes
Enterprises running on AGate today
Real outcomes from organisations that standardised AI governance through AGate, in banking, life sciences, and global technology.
Success Story · Banking
NLB scales AI agents with enterprise-grade governance
Slovenia’s largest banking group rolled out AI agents across the organisation with bank-grade security and full cost control. Adastra delivered the platform in five months.
- Shadow IT and agent sprawl eliminated from day one
- Full audit trail on every AI request, compliant with NIS2, DORA, and GDPR
- Role-based access via Entra ID; spend caps per team and department
- Multi-model AChat deployed company-wide with a branded interface
International Pharma · Life Sciences
Group-wide GenAI governance with full visibility into budgets and interactions.
Global IT & Consulting · Technology
Company-wide AI chat with department budget controls and full observability.
Deployment
Live in 10 to 20 days
Deployed in your cloud tenant and running on real workflows in weeks, not quarters.
Deploy in your tenant
Install via Terraform, connect SSO, and point every provider at one governed endpoint.
Validate on real workflows
Switch on monitoring and per-team spend tracking, test failover, and review your first audit logs.
Scale across the org
Roll out governed AI to every team with full accountability and an audit dossier ready to export.
Why Adastra
Built by a team that has shipped enterprise AI for 20+ years.
AGate is enterprise infrastructure from Adastra, a global AI practice with 150+ engineers and 450+ projects delivered. It is built by the same team that puts enterprise AI into production every day.
Trusted partnerships
20+
Years delivering AI solutions
150+
AI engineers & developers
450+
AI projects executed globally
40+
Countries where we have delivered
Get it now
Ready to take control of your AI?
Get your AI Mission Control up and running in 10 to 20 days. A live demo with the Adastra team, no pitch deck, just your questions answered.
- Guided product demo with your data
- Architecture review for your use case
- Pricing and packaging tailored to your team
Talk to an AI governance expert
Our team will help you design a governance architecture that fits your stack, meets your compliance requirements, and scales with your AI ambitions.
FAQ
Questions enterprises ask us
The questions we hear most from security, platform, and compliance teams.
AGate runs inside your own cloud tenant on Azure or AWS, or fully on-premises. Your data never leaves your tenant, so prompts, responses, and logs stay under your control. EU data residency is supported for regulated workloads, and the same governed deployment works across banking, pharma, and public-sector environments with strict sovereignty requirements.
AGate deploys in 10 to 20 days. It installs in your cloud tenant through Terraform, connects to your existing SSO, and routes every provider through one governed endpoint. You validate it on live workflows during the second month, then scale governed AI access across the organisation from month three, with an audit trail ready from day one.
No. AGate adds a governance layer across the stack you already run. Keep AI Foundry and your OpenAI deployments on Azure, keep Bedrock and SageMaker on AWS, and keep your existing models, regions, and tooling. It works with LangChain, LlamaIndex, and any OpenAI-compatible SDK, so nothing has to be migrated or rebuilt to get governed.
AGate supports OpenAI, Anthropic, Azure, Google, AWS, and Mistral, and more, all behind one governed API endpoint. Teams switch models in a single click without changing code, and on-premises models are supported with full data sovereignty. Because routing is centralised, you can add or swap providers later without touching the applications that depend on them.
Users authenticate through your existing SSO, either Entra ID or Okta, with role-based access enforced on every request. Each team gets a single API key, so credentials never end up scattered across repositories or shared in plain text. Access, spend, and audit are all tied to identity, so you can gate models and cap budgets per team or department.
Yes. Claude Code and Cline are tested and approved with AGate. They connect through the gateway’s OpenAI-compatible and AWS Bedrock endpoints, so authentication, spend tracking, and load balancing are handled by the platform rather than each developer. Engineering teams get governed access to AI coding assistants without scattering keys or losing visibility into cost and usage.
Pricing and packaging are tailored to your team size and usage rather than a fixed per-seat list price. Request a demo and the Adastra team will review your architecture, expected request volume, and the providers you plan to route, then walk you through a pricing model that fits. There is no obligation and no pitch deck, just answers.
Yes. AGate is SOC 2 ready, GDPR-compliant, and built for the EU AI Act, with every request authenticated, logged, and auditable. It runs entirely inside your tenant, so data never leaves your control, and it maps directly to NIS2, DORA, and MiFID obligations, giving compliance and security teams a single, exportable audit trail for every AI interaction.