How It Works
We select the right Azure OpenAI models for your use case — GPT-4o, o1, or embeddings — and deploy them into your Azure subscription with correct regional configuration and capacity planning.
Your application is integrated with Azure OpenAI via Managed Identity authentication, Private Endpoints, and Content Safety filters — meeting enterprise security requirements without proxy workarounds.
We run load tests, evaluate response quality against ground truth datasets, optimise system prompts, and configure token cost monitoring so you go live with confidence.
What's Included
Deploy GPT-4o, o1, and embedding models into your Azure subscription with controlled versioning, blue-green deployment support, and capacity reservation planning.
Replace API key authentication with Azure Managed Identity — eliminating secret sprawl, enabling role-based access control, and meeting enterprise security policies.
Route all Azure OpenAI traffic through Azure Private Endpoints — ensuring no LLM traffic traverses the public internet, critical for regulated industries and sensitive data.
Configure Azure AI Content Safety filters at the gateway level — detecting and blocking harmful inputs and outputs with customisable severity thresholds per deployment.
Implement prompt compression, response caching, model routing logic, and Azure Monitor cost dashboards — reducing token spend without sacrificing output quality.
Wrap your Azure OpenAI integration in a Prompt Flow pipeline — enabling versioned prompts, batch evaluation, A/B testing, and structured observability across all LLM calls.
Who It's For
Teams who have been approved for Azure OpenAI but are still running API calls directly without proper security configuration, monitoring, or cost controls in place.
Engineering teams integrating GPT-4o or o1 reasoning models into existing applications — you need proper deployment architecture, not a quick API key swap.
Organisations in financial services, healthcare, or government that must meet strict data residency, network isolation, and access control requirements around LLM usage.