Pierre-Eliott Lallemant knows the problem cold. Small sales teams scroll through endless LinkedIn profiles, hunting for anyone who might conceivably respond to a pitch. Most automation tools just help them spam faster.
So when Lallemant and his co-founders built Gojiberry AI—a Y Combinator-backed startup—they started from a different premise entirely. What if software didn't just automate outreach, but actually knew when to reach out?
The company calls it a "GTM Brain," which sounds like startup hyperbole until you look under the hood. Gojiberry monitors more than 30 buying signals on LinkedIn: job changes, competitor engagement, funding announcements, hiring sprees, even the content someone's been liking lately. When a prospect lights up—say, a new VP of Sales just landed at a Series B company—the system notices, scores them for fit, and drafts a message tied to that exact moment.
No mass blasts. No generic templates. Just context.
The automation picks up from there, running follow-ups until a meeting gets booked or the thread goes cold. It syncs with HubSpot and Pipedrive, pulls enrichment data from over 15 providers, and builds what the company calls an "email waterfall" to route around bounce rates and spam filters.
According to the company's self-reported launch materials, Gojiberry has crossed 1,000 paying customers and hit $112,000 in monthly recurring revenue, with 44% month-over-month growth. The founders claim they've scaled from zero to $1.4 million in annualized revenue in nine months—figures that remain unaudited and unverified by third parties, but consistent with their traction on Product Hunt, where Gojiberry topped the daily charts in early March with over 400 upvotes.
Those numbers matter less than the behavior they suggest: teams are paying for intent detection, not inbox flooding.
Talking to Claude to Run Your Prospecting
Perhaps one of the most revealing features is Gojiberry's Model Context Protocol integration with Anthropic's Claude. Users can now control their LinkedIn prospecting by simply talking to the AI assistant. Want to run a search? Analyze last week's campaign performance? Draft a message to prospects who just raised a Series A?
Ask Claude. It routes the command through the MCP layer to Gojiberry's platform and executes.
The company published a setup guide showing how to get it running in under two minutes. No coding, no API wrangling. Just a conversational interface layered over the prospecting engine. It's unusual, bordering on experimental, but it tracks with Gojiberry's broader philosophy: let the machines handle the grunt work while humans focus on the actual conversation.
Whether sales reps want to talk to an AI to manage their outbound is another question.
The Team Behind It
Lallemant serves as CEO. His co-founders are Romàn Czerny (CMO) and Dylan Teixeira (CTO), both of whom have exits under their belts. Lallemant and Czerny previously co-founded and exited CoCo AI; Teixeira sold Edusign last year. The seven-person team is listed in Y Combinator's directory as San Francisco-based with a European presence, likely indicating a distributed setup, common enough these days.
In a podcast interview from late April, Lallemant and Czerny said they're aiming to double ARR before Demo Day, then raise a proper funding round. As of now, no external round has surfaced beyond the standard YC investment.
One Tool Instead of Five
Gojiberry is positioning itself against an entire stack. Small sales teams currently cobble together data platforms (Clay, Apollo), email sequencers (Instantly, Smartlead), LinkedIn scrapers (Expandi, Dripify), and CRMs (HubSpot, Salesforce). The pitch: why juggle five tools when one system can detect intent, personalize messaging, and learn what works across your whole org?
The Pro plan runs $99 a month for two LinkedIn senders and unlimited campaigns. Custom pricing kicks in for teams with five seats or more.
Competitors acknowledge Gojiberry's intent-driven edge but point out the limitations of a LinkedIn-first approach—teams running multi-channel campaigns across email, calls, and direct mail still need additional tools. And the company's self-reported claim of "2–5x higher reply rates" comes from internal data and customer testimonials, not third-party benchmarks or independent verification.
Still, for solo founders and lean B2B teams tired of spraying cold emails into the void, an AI that waits for a warm signal makes a certain kind of sense.
The Open Questions
What happens at scale? The system's supposed to learn—track what messaging works, which signals convert, how different personas respond—but machine learning models need volume and time. Whether Gojiberry's "brain" can actually get smarter as it ingests more data from more customers remains an open question.
Then there's LinkedIn itself. The company emphasizes EU hosting and includes a safety FAQ on its website, carefully noting it has no affiliation with LinkedIn. Fair enough. LinkedIn's API terms have tightened over the years, and automation tools live in a perpetual gray zone. Gojiberry's approach—monitoring public signals rather than mass-messaging—feels less aggressive than older-school scrapers, but the platform's tolerance is never guaranteed.
For now, though, the product is live. The growth curve is steep. Customers are paying. And the founding team seems to have tapped into something real: the exhaustion small sales teams feel when the only option is outreach by sheer volume.
Whether the "GTM Brain" can keep learning—and whether salespeople will trust an AI to handle the hardest, most human part of their job—will determine if Gojiberry becomes the next essential tool or just another piece of the fragmented stack it's trying to replace.
