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Use Case

Centralize and Reliable Customer Responses Without Multiplying Tools

How a 30-100 person SMB unified customer support across multiple channels, ensuring consistent, accurate responses while reducing response time by 40%.

Client Context

An SMB with 30-100 employees (SaaS, B2B services, industrial, distribution) receiving customer requests via:

Email
Direct customer inquiries
Forms
Website contact forms
Slack / Teams
Internal communication channels
Basic Ticketing
Simple support tools

Responses involve:

  • Support team
  • Operations
  • Sometimes sales or management

The company had tried:

  • • Templates
  • • A chatbot
  • • An internal copilot

But nothing was truly reliable.

The Problem

1. Responses Are Not Consistent

Depending on who responds:

  • The message changes
  • Rules are not the same
  • Some information is outdated

👉 Commercial and brand image risk.

2. AI Exists... But Is Not Controlled

Teams sometimes use:

  • ChatGPT
  • Internal prompts
  • Tools not connected to real data

Result:

  • • Plausible but false responses
  • • No traceability
  • • No clear rules on what can or cannot be said

3. Too Much Time Wasted

Teams spend time:

  • Re-reading
  • Reformulating
  • Verifying
  • Correcting

The O137 Solution (SMB Version)

O137 is used as a response control system, not as a simple chatbot.

👉A single logic
👉Connected to real data
👉With clear rules

1. Connection to Internal Sources

O137 connects to:

  • Documentation base
  • Standard contracts
  • Customer database
  • Previous tickets

👉 A single source of truth.

2. Response Orchestration

For each request:

  • O137 analyzes the context (customer, contract, subject)
  • Selects the right information
  • Chooses the level of automation

3. Decision Before Response

O137 decides:

  • Automatic response possible
  • Response proposed for validation
  • Human escalation necessary

Based on:

  • • Risk
  • • Customer
  • • Subject

4. Interchangeable Models

  • Fast model for simple FAQs
  • More precise model for sensitive subjects
  • Automatic fallback

The team doesn't see the models—they see the confidence level.

5. Simple Traceability

Each response is:

  • Explained
  • Sourced
  • Historized

👉 Useful for training and quality.

Concrete Results

-40%
Time spent responding
Homogeneous Responses
Consistent messaging across all channels
Fewer Errors
Reduced incorrect information
Better Served Customers
Improved customer satisfaction

What SMBs Gain

A Single, Reliable Voice
Consistent messaging across all customer touchpoints
AI That Helps Without Risk
Controlled, traceable AI assistance
Less Mental Load
Teams focus on value-added work
More Professionalism
Elevated brand image and customer experience

In Summary

Not a gadget chatbot

Not an automated FAQ

A system that decides how to respond to customers