All offers

Fixed-scope build

Sovereign AI

AI Gateway Blueprint for model routing and policy control

In six weeks, every AI model your organization uses gets one governed, observable entry point — complete with routing, policy enforcement, cost control and an audit trail.

Duration

6 weeks

Usual next step

Sovereign AI Platform Proof of Value

The problem

AI adoption inside a large organization does not arrive as a program. It arrives as twelve teams with twelve API keys, three model providers, no shared view of cost, no consistent guardrails, no audit trail, and no way to answer the question “which of our systems sends data to which model”.

By the time someone asks that question, usually a CISO or an auditor, the answer takes weeks to assemble and nobody likes it.

What we build

A gateway: one governed path between your applications and every model they use.

  • A single API surface for your teams, so switching or adding a model provider is a configuration change rather than a project

  • Routing and model selection: route by use case, data classification, cost, latency, or quality, with rules you control

  • Policy enforcement at the gateway: which teams may use which models, which data classifications may leave which boundary, what gets filtered on the way in and on the way out

  • Cost visibility and control: per-team, per-application, and per-use-case token and cost accounting, with budgets and limits that actually enforce

  • Full audit trail: every request attributable, retained to your policy, ready for an audit question

  • Observability: latency, error rates, token consumption, and quality signals, in the observability stack you already run

  • Resilience: fallback and failover across providers, so a single provider outage does not take out your AI-dependent services

  • Deployed on your infrastructure, sovereign or otherwise, entirely on open source, as code, with no dependency on us

Why this is usually the right first platform investment

It is the cheapest way to turn uncontrolled AI adoption into governed AI adoption without slowing any team down. Teams keep building. You get control, cost visibility, and an audit trail. And when your data classification requires a European or self-hosted model for a given use case, the gateway is the thing that makes that a routing rule instead of a rewrite.

How it runs

Weeks

Phase

1

Discovery: current model usage, teams, policies, cost, and the target architecture

2 to 4

Build: gateway, routing, policy, cost accounting, observability, audit

5

Onboarding: two to three real teams migrated onto the gateway

6

Hardening, documentation, handover

Who it is for

Organizations where AI usage has spread across multiple teams and providers and now needs governance, cost control, and an audit trail, without a moratorium.

What happens next

The gateway is the foundation layer for a wider AI platform. From here the usual paths are a Sovereign AI Platform Proof of Value for the first governed use case, or a Platform Operations Partnership for day-2 ownership.

Interested?

Outline where you are and what you are trying to settle. We will answer with a scope, a price, and an honest opinion on whether this blueprint is the right choice.