The implementation and use of AI assistants can be carried out reliably, scalably, and quickly, without a heavy project. In a four-week risk-free pilot, you have the opportunity to learn how your materials work with an AI assistant and what kinds of use cases assistants tailored to your specific needs can support.
Why and how our implementation works
Our AI Workforce solution is built on Microsoft's cloud architecture so that it combines security, transparency, and rapid deployment, without a heavy IT project.
Here's a summary of how and why this approach produces measurable business value from the very beginning.
1. Source-grounded AI (RAG)
The assistant doesn't guess but always responds based on real sources — the organization's own documents, manuals, and databases.
This is called Retrieval-Augmented Generation (RAG). It means that every answer includes a link to the original source, and any statements that cannot be verified are simply left out.
Result: hallucinations are structurally prevented, and users can trust every response.
2. "Show the source or don't respond"
Answers are verified, and if they are not supported by the material, the assistant says so directly. This makes AI a reliable tool. The user can check the source with one click and see where the information comes from.
3. Control and organization's data in secure hands
Assistants operate in Avatars Intelligence's enterprise-level Azure environment, and the service can be accessed through Microsoft Entra ID login (SSO).
All processing can take place within the EU Data Boundary, following enterprise-level data protection requirements.
4. Transparent quality and continuous improvement
All responses are tracked with real-time metrics (e.g. accuracy, coverage, groundedness deviations), which enable continuous improvement as usage grows. The organization's dashboard provides an instant overview of how well the AI assistants respond to users' questions.
5. Lightweight and fast architecture
The entire implementation runs on Microsoft Azure native services:
- Azure AI Search – search and indexing
- Azure Functions & Web App – application logic and user interface
- Cosmos DB – database
- Application Insights – monitoring and audit
- Azure OpenAI / Azure AI – language models not trained on customer data
This combination enables a fast start, controlled expansion, and scalability in a secure and functional way.
This is why our implementation works — and why our customers see results already within the first four weeks.
