Two sales reps, two different ways of dumping a half-empty contact into our outreach CRM. Here's how we ended up building two n8n workflows to fill that gap, and more importantly, everything that broke along the way: an endpoint that returns an empty CSV instead of JSON, an editing bug that silently duplicated parameters, a rate limit we hit twice, and a "job title in English" that turned out not to be a bug at all.
At Dolist, the sales team runs its prospecting sequences in Lemlist. Every sequence generates manual tasks (a call, a LinkedIn message, a profile visit) and Lemlist displays them perfectly... in Lemlist. The problem is that nobody lives in Lemlist all day. Here's how a small n8n workflow was enough to land these tasks where attention already is: Teams.
There comes a point where commercial databases are no longer enough.
They can tell you a company exists. They sometimes give you an industry, a size, a website, a LinkedIn account, a few contacts.
But they rarely answer the most interesting question:
Why does this company deserve to be contacted right now?
That question is what gradually led me to work on a broader topic: business signal detection using AI, scraping, automated workflows and some RevOps logic. Not to build a magic machine to sell. Not to replace salespeople. But to better prepare sales work, understand the movements of a company, and turn fairly noisy public data into actionable context.
This page is an entry point. It connects several technical experiments around scraping, competitive monitoring, expansion signals and semi-automated prospecting, and explains the overall reasoning behind these projects.
The problem I was trying to solve wasn't technical at first. It was a timing problem.
Some projects start because you have a real problem to solve. Not an abstract idea. A concrete problem that comes back every week.
As part of Signar, I needed to answer a simple question: how do you help a sales team monitor its competitors without spending two hours manually searching LinkedIn, Trustpilot, and websites?
It started with a simple problem to solve: SDRs were spending too much time finding companies, identifying contacts, crafting messages, and following up manually.
The real problem wasn't the sales work itself. It was everything that comes before it: the preparation.