Read the request
The agent extracts customer question, deadlines, attachments, and constraints from email or form.
AI agent quote preparation
An AI agent that completes quote requests before sales, estimating, or operations begins. Less back-and-forth, better briefing, and a sharper proposal faster.

EERSTE PILOT
Quotes get stuck when needs, constraints, and open questions remain spread out.
THE HOOK
Your AI colleague can do a lot. In the 4-week onboarding period we teach it, together with you, the work that keeps piling up every week: completing requests, tracking files, following up leads, preparing quotes or supporting production.
After that it grows into new tasks. Industries are examples; the real entry point is the workflow that keeps stalling.
WORKFLOWS THAT COST MONEY OR TIME
This page focuses on recurring work. No generic AI promise, but concrete tasks that return every week and become measurable fast.
The agent extracts customer question, deadlines, attachments, and constraints from email or form.
Missing information is made visible before anyone starts on the quote.
The customer receives clear questions so sales doesn’t have to guess.
Deviations, unclear agreements, and dependencies are brought to the surface.
Sales, estimating, or operations gets one overview with needs, context, and action points.
Status, owner, and next step remain visible until the quote is ready.
WHY THIS MATTERS COMMERCIALLY
Most companies lose time not to one big task, but to dozens of half-finished questions: incomplete requests, loose emails, forgotten documents, feedback without an owner and leads that get followed up too late.
More complete quote requests
Measurable in less back-and-forth, faster follow-up and better handover to the person doing the work.
Less back-and-forth
Measurable in less back-and-forth, faster follow-up and better handover to the person doing the work.
Faster handover to the team
Measurable in less back-and-forth, faster follow-up and better handover to the person doing the work.
BEFORE MATCH-AI
AFTER MATCH-AI
FIRST 2 WEEKS
Start with one type of request that often comes in incomplete.
Which questions does the agent ask, where does it stop and when does it go to a human?
Email, form, Telegram, Drive, CRM or existing customer documents.
First version at work, with a clear feedback loop for improvement.
SAMPLE OUTPUT
A good AI colleague does not send a long answer. It delivers a usable handover that someone can act on straight away.
// Sales, estimating and operations
Summary: Quotes get stuck when needs, constraints, and open questions remain spread out.
Missing info: planning, budget, contact person, attachments
Suggested action: create a task, request the missing info and route it to the owner
Needs a human for: pricing agreements, exceptions and substantive judgement
Keep building
These internal links connect AI agents, workflow automation and process automation. Visitors choose faster and search engines understand better which pages belong to the same AI colleague cluster.
Recommended next step
Ensure new inquiries reach sales faster with context and next steps.
Recommended next step
Turn request, briefing, and review into one fixed workflow.
Recommended next step
Start with one concrete quote pilot before you scale further.
Quick answers to the main questions.
How your AI colleague works
Cyrill distributes the work across one AI colleague per department. They work in your own systems, share one memory and learn from every task your colleagues do with them.

THE PEOPLE BEHIND MATCH-AI
Match-AI is a team of co-owners with a background in sales, marketing, finance and technology, supported by specialists in support and marketing. Every project gets a dedicated contact person who thinks along about process, adoption and results.
Peter van de Groep
Commercial contact at Match-AI
YOUR CONTACT
Book an intake. Together we choose the first pilot and define what the AI colleague must deliver.