Answer the predictable questions
Start times, rules, documents, registration, payments, organisational details — the agent answers from the marathon's own knowledge base.
An AI agent that runs the first line of support for one of the largest running events in Central Asia. Participants write into WhatsApp and Instagram with the same questions every day — when does it start, what are the rules, how do I pay, where do I pick up the pack — and the team behind the marathon could not keep up. The agent answers nine out of ten of those messages on its own. The tenth one — a refund request, a complaint, a VIP, a sensitive case — gets picked up by a human with a clean summary already in their inbox.
A marathon at this scale pulls thousands of participants writing in at the same time across several channels. The call centre never had a chance to be fast on the easy stuff, which meant the difficult cases — complaints, refunds, conflicts — landed on already overloaded operators.
The goal was not to replace the team. It was to take the predictable ninety percent off them so the remaining ten could be handled properly.
The agent picks up every message across WhatsApp Business API and Instagram (via Meta Business Suite) and answers from the marathon's knowledge base — rules, schedule, registration, payment, documents.
A second layer watches for cases that need a person: complaints, threats, VIPs, refunds, withdrawals, anything that looks unusual. When one shows up, the agent stops, summarises the conversation, attaches the reason, and pings the responsible manager on Telegram or WhatsApp. The human walks in with context, not from zero.
Start times, rules, documents, registration, payments, organisational details — the agent answers from the marathon's own knowledge base.
Complaints, threats, conflicts, VIPs, refunds, withdrawals, repeat contacts — the agent recognises them and stops automation.
The manager gets the reason for the escalation plus a short recap of the conversation, so the takeover is one step instead of a re-investigation.
A manager confirms themselves once via a code phrase or a one-time link. After that they're on the alert list and get notifications automatically.
WhatsApp Business API for the main participant flow, Instagram via Meta Business Suite, Telegram for the team side.
The agent runs on Python with Google ADK as the multi-agent layer — agent logic, conversation scenarios, routing of complex cases, prompt architecture all live there. The knowledge base is the marathon's FAQ, rules and registration policies.
On the quality side we treat support like a moving target: we collect reference conversations, build datasets from the best operator replies, and run an AI Judge that scores the agent's answer against the reference. The point is not "AI sounds smart" — it is "AI sounds like the team that already does this well".
Roughly nine out of ten participant conversations close inside the agent. Operators only see what actually needs them.
Refunds, complaints, conflicts and VIPs are detected and routed to the responsible manager with a summary attached.
Participants get an answer at any hour, in any channel, without the marathon hiring a night-shift operator.
We reply within one business day. Then Azamat joins every first call personally, so you get an honest scope, budget, and fit from the person responsible for delivery.