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Case · Health & wellness · United States · 2025

RAG bot for a 42-day program

Program days
42
On the methodology
RAG
Channels
3
The project in facts
FormatRAG bot for a 42-day program
Contextknows the participant's day and phase
Channelsweb · Telegram · WhatsApp
StackMastra · Claude
Challenge

The same questions — for 42 days straight.

Participants in a 42-day program kept asking about the day, phase and dosing — answers had to be context-aware, multilingual and compliant.

We built a RAG bot grounded in the program methodology, on Mastra and Claude. It knows which day and phase a participant is on and answers for that exact stage, only within the approved materials; sensitive questions are not improvised but escalated to a live coach together with the context. It answers in the participant's language on the web, in Telegram and in WhatsApp.

Before, routine questions went to coaches, an answer depended on a coach being free, and there was a real risk of answers drifting outside the methodology. Now the bot closes the routine within the methodology around the clock in three channels, the guardrails keep it inside the approved base, and coaches spend their time on coaching rather than on "which day am I on".

Context

What was in the way

  • ✗Participants asked the same things daily: which day, which phase, what to take
  • ✗Answers had to stay within the methodology — no improvisation
  • ✗Coaches spent time on routine questions instead of coaching
Capabilities

What the system does

01

Methodology-grounded answers

RAG over the program base — the bot answers only within approved materials.

02

Day and phase context

Knows which day of the program the participant is on and answers for that exact stage.

03

Guardrails and escalation

Sensitive questions are not improvised — the conversation goes to a live coach.

04

Multilingual

Answers in the participant's language on web, Telegram and WhatsApp.

What's inside

How we roll it out.

Discovery

Requests and access analysis

We study historical requests, verify CRM and API access, and score the automation potential.

Pilot

A slice of real traffic

The agent runs on part of the live requests with weekly syncs — real dialogues, not a demo.

Launch

Metrics and scale-up

We evaluate volume, response speed and escalation share — then expand the agent to full traffic.

Results

Before → after

Before
After
Routine questions went to coaches
The bot closes them within the methodology
An answer depended on a coach being free
Available around the clock in three channels
Risk of answers outside the methodology
Guardrails and human handoff

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