AI API & Model Integration

When every application calls model providers directly, the organisation ends up with keys scattered across code, no view of total spend, no consistent logging, and a hard dependency on one vendor's pricing and availability. Data handling becomes impossible to describe, because nobody knows which application sends what where.

Organisations with several AI features built by different teams, products that need to offer a choice of models, regulated environments that must keep some data on self hosted models, and finance teams asking why the AI bill doubled.

We put one gateway between your applications and the models. It holds the credentials, enforces which data classes may go to which provider, routes requests to the appropriate model, caches where safe, applies rate limits and budgets, and logs every call with cost and latency. Self hosted open models sit behind the same interface for data that must not leave your environment. Switching a provider becomes a configuration change.

We inventory the existing AI integrations and data flows, agree on the data classification and routing rules, and deploy the gateway in your environment. Applications are migrated one at a time. Where self hosting is required we size and deploy the model infrastructure with our infrastructure practice. Dashboards for spend and usage are part of the handover.

One controlled door to every model you use.

• Model gateway with authentication, routing, caching, limits and logging
• Data classification and routing policy, enforced in the gateway
• Spend and usage dashboards, and self hosted model deployment where needed

A single answer to what the organisation spends on AI and where its data goes, resilience against any one provider's outages or price changes, and faster delivery of the next AI feature because the plumbing already exists.