Pierre-Eliott Lallemant is already a few steps ahead of most founders.
He built and sold a SaaS company, scaling it to $500K in ARR before walking away with cash in hand, and a deep well of frustration that would prove even more valuable for what came next.
Sales was the sticking point.
Not closing, but sourcing. Every day, he and his co-founder wasted hours tracking down leads. LinkedIn. Cold lists. Outdated databases. It all slowed them down.
So when it came time to start something new, they went back to that exact pain and built something to fix it.
Why GojiberryAI Exists
GojiberryAI is an AI-powered lead engine that watches what your prospects are actually doing.
It scans LinkedIn for high-intent signals.
Like when someone changes jobs, interacts with a competitor’s post, or announces a funding round. Those signals usually mean: someone’s open to buying.
Once the signal’s spotted, GojiberryAI finds contact info (email, phone, and more) and pipes it straight into your CRM. It removes all the grunt work of traditional prospecting, while still keeping your outreach warm.
The product is aimed at founders and sales teams that don’t have time to sift through 100 profiles to find one opportunity. Instead, they get a focused stream of leads already showing interest; just not directly to them yet.
It’s outbound that feels like inbound.
The First Launch Failed. Completely
It’s easy to look at success and miss the early misfires.
Pierre-Eliott’s first version of GojiberryAI had nothing to do with lead gen. It was positioned as an AI sales assistant that would auto-fill CRMs and take meeting notes. On paper, that sounded great. In practice, it bombed.
Despite racking up a 2,000-person waitlist, the product made zero sales.
The lesson? Interest doesn’t equal intent. Waitlists can look like traction but mean very little if they’re not tied to a clear pain or buying moment.
Pierre-Eliott admits it freely: they thought they had a product. What they had was just attention.
Pivoting Toward a Real Problem
After the failed launch, the team circled back to what they’d lived through: the time-suck of finding leads.
That’s when the idea clicked. Instead of making sales easier at the end of the pipeline, they’d make it easier at the start.
They dropped the AI note-taker, shifted focus to live intent signals, and rebuilt the product to deliver sales intelligence, not just automation.
Within 60 days of the pivot, they hit their first big milestone: 100+ paying customers. And this time, the traction was real. Customers were converting because it worked.
A Few Reasons It Worked This Time
GojiberryAI doesn’t try to replace sales.
No, it makes sales teams faster by focusing their time where it matters. By using live intent signals, it avoids the noise of typical scraping tools and keeps leads warm.
This approach is part of a growing trend in outbound tools: action over abstraction.
It’s not about databases. It’s about context. A lead with no timing is a dead end. But a lead showing intent? That’s a foot in the door.
Their earlier failure helped refine the product, but it also helped sharpen their messaging. Now they’re not promising “AI for sales.”
They’re solving a simple problem: how to stop wasting time on cold leads.
Advice for Founders From Pierre-Eliott’s Journey
There’s a lot here for other early-stage founders, especially those building SaaS tools.
- A waitlist means nothing if no one’s paying
- Don’t build what sounds cool, build what the market needs
- Solve the first problem in the funnel, not the last
- A pivot isn’t a failure, it’s proof you’re listening
Pierre-Eliott and his team moved fast, admitted when the first idea didn’t work, and built something better by going back to their own biggest frustration.
And this time, the market agreed.
You can check out GojiberryAI or follow Pierre-Eliott on LinkedIn.
