Enterprise AI

An AI chat platform that grows with the business

A secure, extensible AI chat platform

Most Enterprise AI chat initiatives don't last because the architecture gets built for one use case, and every new one means rebuilding identity, audit logging, and deployment pipelines from scratch. With AI adoption accelerating across business units our client needed a platform that survives the proof of concept and scales with the business.

Here's how we built a governed agent platform where extensibility is structural.The plugin model handles the full range of what enterprise users need in a single conversation with answers from documents, live data from backend systems, and actions triggered against them — without any of it hardcoded into the agent.

Defining success early

We resisted the instinct to build for the immediate need only. We created a stable core with every new capability pluggable from day one.

Extend without rebuild

Enterprise AI
  1. The architecture separates and resolves three concerns that are almost always tangled - runtime, management, and plugins. Every section of this platform was designed to eliminate a specific reason enterprise AI projects get abandoned.

  2. 01

    A stateless runtime

    The runtime is a conversational agent built on Azure OpenAI. For each user turn it decides whether to retrieve from a knowledge base, call a live system, or both — with no hardcoded logic about which capabilities exist. That knowledge lives in the plugin registry, keeping the core engine clean and stable.

  3. 02

    Extensibility with different plugins

    RAG for document answers, Tool for live API calls, Hybrid for retrieve-then-act flows, and Prompt for scenario-specific behavior. The management API governs the lifecycle — draft, publish, disable — without touching the runtime. Changes reach production via Storage Queues, no redeploy required.

  4. 03

    Security and visibility

    The admin portal gives non-technical administrators full visibility across plugins, access controls and audit logs. Role-based access is enforced through Entra ID and Managed Identity. Telemetry, alerting and secrets management are unified across every layer

The tech stack

Staying within Azure was a deliberate choice. The client's existing investment in Microsoft tooling across Active Directory, Azure tenancy and compliance frameworks made it the right foundation for governance, not just compute. The stack maps cleanly to the architecture: Azure OpenAI for the model with the enterprise security controls that come built into the Azure estate, AI Search for hybrid retrieval at scale and Functions to provide the serverless execution model for plugins.

The result

An AI platform the business can keep building on

A living Al Chat platform

Enterprise AI
  1. Building with Al is straightforward. Building Agentic Al an enterprise can govern, extend, and operate without rebuilding is the real value creation. Near-term improvements already in progress include maturing compute consolidation across worker functions, deepening RAG quality through evaluation loops and citation accuracy improvements, and extending the admin portal with richer observability dashboards. Each improvement lands without disrupting what is already running as extensibility is an architecture decision, not an afterthought. Beyond the model, it is the architecture around it that makes this a living platform.

Bring us the problem. We'll build the solution.

Tell us where you want to go next. We'll bring the engineers, the process and the Nordic accountability to get you there.

TIQRI / Expertise

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