AI agent on the medical desk: how Sovcombank automates complex calls

Sovcombank has deployed an AI agent in the medical desk of its insurance company. This is not an experimental project to "play with neural networks" but a production rollout of an LLM in a process where mistakes are costly and the customer expects a quick resolution.

Where the agent works

On the line, the operator hears an insured customer explain a medical problem. The agent listens to the conversation and helps the operator work through it:

• Quickly grasp the core of the customer's problem
• Enter medical data into the system correctly
• Preserve the context of the conversation and avoid losing important details
• Suggest the next step in the workflow

The operator remains in charge: they make the decisions and bear responsibility. The agent works like an experienced colleague sitting next to them.

Why this is harder than a simple chatbot

In an insurance company's call center, a mistake can lead to a wrong diagnosis, lost customer data or incorrect handling of an insured event. Speed is also critical: the person is waiting for help, and a medical consultation demands attention to detail.

The agent must simultaneously understand medical terminology, the insurance context, data-entry requirements and the customer's state of stress. A regular LLM without special training on real cases cannot handle this.

How it was rolled out

The team did not start with full automation but with support for the operator. The agent suggests input options, offers prompts and clarifies details based on the medical context. Everything goes through the operator, who verifies every step.

"The goal was not just to play with neural networks, but to actually build an LLM into the process," say the developers at

Sovcombank.

The setup process included testing on real calls, collecting feedback from operators and doctors, and iterative improvement. To keep the system from making mistakes, it was trained on examples of real errors and difficult cases.

What this means

AI agents are moving out of the category of amusing experiments and into the category of critical tools in production processes. If even in insurance, where a mistake costs money, a company trusts an LLM to help in conversations with customers, the technology has matured.

The next stage is integrating agents into tech support, legal consulting and credit scoring.