Sales · scenario 1 of 5
B2B prospects that fit, not a longer list
I build research that finds companies matching your ideal customer, judges the fit and builds a short profile with talking points for each. Your reps start with a reason to call, not a list of names.
How it works
- 01 · Event
Criteria defined
You describe the ideal customer once: industry, size, region.
- 02 · Data
Public facts only
Websites are read for the facts needed; no personal database is built.
- 03 · AI
Fit and angle
The AI decides whether the company fits and which of your products matters to it.
- 04 · Action
Profile in the CRM
A short profile and talking points go into your CRM.
- 05 · Check
Weak fits filtered out
Companies that don't clearly fit stop before they reach the rep.
- 06 · Human
Rep reaches out
How to make contact is the rep's decision; the system sends nothing.
What you get
- Reps spend their time on companies that fit, not on searching.
- Every first contact refers to what the company actually does.
- Your CRM grows by checked profiles, not bought lists.
Example
A kitchen-equipment distributor targets hotels with a restaurant in Tyrol. The system notes which run a seasonal kitchen and drafts talking points about it. The rep uses them to call.
Privacy by design
The AI sees only the public company information needed to judge fit. I store the structured profile, not the downloaded pages.
Typical stack
Web search and crawling APIs · LLM with structured output · n8n or Python workflows · your CRM's API
Built into what you already run: your CRM, telephony, n8n instance or cloud stay in place. I can also take over an existing workflow or join a running project.
Often combined with
Describe what slows you down.
You get back what to automate first — and what not to.
Have a defined project already? Send the brief.