Your prompts stay under your control.
The entire platform runs in a secure container inside your own cloud. You can see every piece of it — and you decide whether a prompt ever leaves your four walls.
The whole platform runs in your Azure account
Using Azure as the example: we deploy into your account, into a single resource group your team can see. Explore each piece below.
Tap any resource to see how it keeps your prompts under your control.
AuditionAI
Containerized app
Our application ships as a sealed container and runs inside your App Service. This is where prompts are received and where your data privacy and sovereignty policies are enforced before anything moves.
The policy checkpoint for every prompt.
Where do your prompts go?
Pick models that run directly in Azure and keep everything in your four walls — or choose a frontier model from outside Azure when you want it. Flip the switch to see the difference.
Your prompt never leaves your environment.
Your prompt goes to a model running inside your own Azure account, and the response comes back — without ever crossing your boundary.
Your policy lives in every assistant
Inside Audition AI, you configure Assistants and Connectors to apply the data privacy and sovereignty rules your company sets — so the right boundary is the default, automatically.
Assistants
Each assistant is built for a job — and carries the rules for that job. Pin sensitive assistants to in-Azure models so their prompts can never leave your environment.
Connectors
Connectors decide what data an assistant can reach and where it can send it. They honor your existing access controls, so the AI only ever sees what the person already can.
Sovereignty policy
Set the rule once: which models are allowed, for which teams, with which data. Every prompt is checked against that policy before anything moves.
Runs in your cloud
Deployed as a sealed container inside your own Azure account — not a shared, multi-tenant service.
Nothing hidden
Everything lives in a resource group your team can open and inspect in the Azure portal.
Your keys, your data
Prompts, history, and files are stored in databases and storage accounts you own and control.
You choose the boundary
Keep prompts in your four walls with Azure models, or allow external models — on your terms, by policy.
Want the deeper detail? See Transparency & Audit Trails, Governance & Compliance, and AI Models.
Can you use models and capabilities outside your environment?
Yes — and it's not a security compromise. When you choose to reach outside Azure for frontier models like Claude or Gemini, or external services like Perplexity, those calls are org-controlled, logged, and compliance-reportable.
Claude (Anthropic)
Outside AzureOne of the strongest reasoning models available. Used where deep analysis, nuanced writing, or complex multi-step tasks matter most.
- Research synthesis
- Document drafting
- Policy Q&A
Gemini (Google)
Outside AzureGoogle's frontier model — capable across long-context reasoning, code, and multimodal tasks including image and document understanding.
- Long-document analysis
- Multimodal workflows
- Code generation
Every external model and service — same three guarantees
Org-controlled
Admins choose which external models and services are available. Nothing is enabled by default — it's an explicit decision.
Fully observable
Every call to an external model or service is logged: who triggered it, what was sent, what came back, and when.
Compliance reportable
Logs are structured and exportable for audit. Your compliance team can see exactly what left your environment and why.
See it in your own environment
We'll walk through exactly how Audition AI deploys into your cloud and how your prompts stay under your control — using your real requirements.