Mission Control for Your Enterprise AI.
Your teams already use AI. With AGate, you can govern all of it.
Trusting Adastra's AI expertise
The Challenge Ahead
AI Is No Longer Just a Chat.
AI is taking actions inside your systems. Your teams use ChatGPT, Copilot, Claude, and Gemini every day. Your developers connect AI to SAP, SharePoint, and your CRM. Nobody has a single view of what it does, what it costs, or what it risks.
Without a governed layer, four risks compound fast.
Shadow AI
Unapproved tools spread beyond anyone's view.
Agent sprawl
Agents multiply faster than you can govern them.
IT overload
Teams drown in one-off AI rollouts.
Runaway cost
AI spend climbs with no caps or alerts.
91%
of organisations encountered sensitive data leakage risk
Check Point, 2025
€5–20M
potential fine per incident under NIS2 and AI Act
per regulatory breach
30–50%
of GenAI "innovation" time lost to compliance overhead and rework
Centralised governance can virtually eliminate it. McKinsey, 2025
The Platform
Two Components, One Platform
AGate is your GenAI control layer with two key components: LLM Gateway to govern every model request and AChat to put compliant AI in every team's hands.
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
AChat
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
Reference Architecture
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. AGate Adds Full Governance.
Deploy AGate into the cloud you already run. Keep your existing models, regions, and tooling. AGate layers governance on top, with no migration.
Use Cases
Built for every AI initiative in your enterprise
From banking compliance to pharma governance to enterprise-wide AI platforms: AGate adapts to your operating model and regulatory environment.
Scale AI agents without losing control
Stop shadow AI and agent sprawl. Audit every request, gate access by role, and cap spend, mapped to NIS2, DORA, and MiFID.
Govern GenAI across the entire group
See every team's AI usage and spend in one place. Plug in existing use cases without rebuilding your infrastructure.
Build your internal AI platform in weeks
Give 2,500+ people governed self-service AI, with department budgets and compliance built in. No custom auth to write.
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.
Proof Points
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 branded interface
80%
faster AI use-case implementation
5 months
to full production platform
100%
data security and auditability
International Pharma
Life Sciences
5 months
to a production AI platform
Group-wide GenAI governance with full visibility into budgets and interactions.
Global IT & Consulting
Technology
2,500+
people on one governed platform
Company-wide AI chat with department budget controls and full observability.
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
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.
Aleš Gorišek
AI Architect, NLB Group
FAQ
Questions enterprises ask us
01 Where does AGate run?
In your own cloud tenant (Azure or AWS), or fully on-premises. Your data never leaves your tenant, and EU data residency is supported for regulated workloads.
02 How long does deployment take?
AGate installs in your cloud tenant via Terraform in 10–20 days. You validate it on live workflows in the second month and scale governed AI access across the organisation from month three.
03 Do we have to replace our existing AI stack?
No. Keep AI Foundry and your OpenAI deployments on Azure, keep Bedrock and SageMaker on AWS. AGate adds a governance layer across all of them. It works with LangChain, LlamaIndex, and any OpenAI-compatible SDK.
04 Which AI providers and models are supported?
OpenAI, Anthropic, Azure, Google, AWS, Mistral and more, all behind one governed API endpoint. Teams can switch models in one click, and on-premises models are supported with full data sovereignty.
05 How do users authenticate?
Through your existing SSO (Entra ID or Okta) with role-based access. Each team gets a single API key, so no credentials end up scattered across repositories.
06 Can developers use AI coding assistants through AGate?
Yes. Claude Code and Cline are tested and approved with AGate. They connect through the gateway's OpenAI-compatible and AWS Bedrock endpoints, with authentication, spend tracking, and load balancing handled by the platform.
07 How is AGate priced?
Pricing and packaging are tailored to your team and usage. Request a demo and we'll walk through your architecture and a pricing model that fits.
Ready to take control of your AI?
Get your AI Mission Control up and running in 10 to 20 days. Live demo with the Adastra team, no pitch deck, just your questions answered.
Contact
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.
- Guided product demo with your data
- Architecture review for your use case
- Pricing and packaging tailored to your team