Case Study
Twing Group AG – Sales Automation with AI
How Swiss SME Twing Group AG saves over 150 hours per month with AI automation
70%
Time saved on quotes
150h
Hours saved per month
~40%
Response rate on reactivation
Project 01
Project 1: Quote Request Automation
Every month, numerous quote requests came in via the website form. Each request required multiple manual steps — review, research, response email, CRM entry, archiving. With the risk of missed steps or exceeded response deadlines.
How the automated process works
Intake & Classification
Form submissions are received via webhook. An AI agent automatically classifies them as valid requests vs. spam.
AI Pre-qualification
The agent analyzes product request, quantity and language, checks article availability and finishing options directly in Bexio, and retrieves current FAQ content.
Response Draft
A personalized initial response is generated — including automated research on the requesting company.
Approval via Slack
The draft lands with full context in the sales channel. A team member reviews the suggestion and approves it with one click — or takes over the request manually.
Automatic Post-processing
CRM entry, advisor assignment, follow-up task and email archiving run fully automated. The design team automatically receives a task in ClickUp with the customer's uploaded logo.
Tools Used
Results
- 70% less processing time per request
- ~12 hours of manual routine work eliminated per month
- Max. 4-hour response time reliably maintained
- 100% process errors eliminated
Project 02
Project 2: Lead Reactivation
The company has thousands of warm leads in the CRM that should be reactivated regularly. Manual, personalized reactivation would be valuable, but is not realistic due to the high volume. Meanwhile, valuable revenue potential remains untapped.
How the automated reactivation works
Dynamic Lead Selection
The target group is defined directly in the CRM. Make.com retrieves the selection dynamically — adjustments in the CRM take effect immediately, without technical changes.
Validation & Quality Logic
Before each send: Is an active advisor assigned? Are they available? Are there valid contact details, opportunities and a relevant email history?
AI-powered Personalization
An LLM analyzes opportunities, previous email history and customer-specific contexts. A highly personalized reactivation email is generated
Delivery & Follow-ups
Delivery status is checked via webhook. If no response, two automated follow-ups are sent. All contacts are fully recorded in the CRM.
Response & Intent Detection
Incoming responses are analyzed and classified by LLM: reorder, quote requested, new opportunity, or no need. The sales team receives the information structured for further processing.
Tools Used
Results
- ~40% response rate on personalized messages
- New opportunities and reorders directly from responses
- ~150 hours of manual effort eliminated per month
- Full transparency for advisors and management
Working with INFLECT led to measurable revenue growth within just a few weeks. What used to take hours, or couldn't be done due to lack of time, now runs automatically.
Andrin Caviezel
Geschäftsführer, Twing Group AG
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