Company profile · 4 min read
Gojiberry AI: intent-led outbound for B2B teams
Gojiberry AI finds high-intent prospects, personalizes outreach, handles replies and books meetings as an AI GTM team for B2B companies.
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
Published · Updated
What it does
Gojiberry AI is an outbound-focused AI GTM team for B2B companies. It finds prospects showing buying or social intent, scores them against an ideal customer profile, enriches the record, sends personalized outreach across email and social channels, handles follow-ups and books qualified meetings. The YC profile describes the longer-term ambition as a system that can also act on inbound leads, website visitors, CRM history and expansion opportunities.
The fit is a lean B2B sales team that has already defined its ICP but does not want to assemble a stack of data, sequencing and SDR tools. Gojiberry is not most useful for a company that has no idea who buys or what a qualified meeting means. Its promise depends on the agent learning from conversion signals rather than simply sending more messages.
Why I’d look closer
The product’s strongest detail is the closed loop: the homepage says the agent detects signals, filters prospects before outreach, coordinates messages and tracks what converts over time. That is more interesting than a generic AI SDR because it gives the campaign a memory. The case-study page lists specific customer stories, including Wispra attributing 60% of weekly demos to intent signals, Mindflow reporting a 31% reply rate, and GTE Localize reporting 100+ meetings. Those are company-published case-study claims, not independent benchmarks.
Gojiberry also publishes substantial company-reported traction. The YC profile says it grew from zero to $2.5M ARR in ten months and serves 2,000+ customers; its launch text contains a different earlier snapshot of $112K MRR, 1,000+ paying customers and 44% month-over-month growth. I would treat these as dated company claims and ask which cohort, period and definition sit behind each number rather than blend them into one metric.
The founders have a repeat-founder and product-growth profile. The YC biographies describe Pierre-Eliott Lallemant and Romàn Czerny as prior founders, and Dylan Teixeira as a former Edusign co-founder whose SaaS business reached multi-million ARR before a 2025 sale. That experience fits an automation product aimed at small sales teams.
What I’d ask
How does Gojiberry obtain intent data, respect opt-outs and protect sender reputation? I’d inspect the exact channel permissions, enrichment provenance, human approval controls and reply-routing behavior. One focused campaign should measure qualified pipeline and downstream conversion—not only reply rate—against a comparable outbound baseline.
My editorial take
Gojiberry is a credible fit for a B2B team that wants an always-on outbound operator and has enough historical signal to teach it. The company-specific case studies make it worth testing; the large traction claims should stay labeled and separate from the buyer’s own pipeline evidence.
Quick facts
| Field | Sourced detail |
|---|---|
| Buyer fit | Lean B2B sales and GTM teams with a defined ICP |
| Workflow | Intent detection, enrichment, outreach, replies and meeting booking |
| Proof signal | Named case studies and company-reported customer/ARR claims |
| Public pricing | Not exposed in the sources checked |
Sources checked
Checked 2026-09-19.
| Source | Used for |
|---|---|
| YC company profile | Product, founder backgrounds and dated traction claims |
| Gojiberry homepage | Current agent workflow and positioning |
| Gojiberry customer stories | Company-published case-study claims |
Cohort context
Gojiberry AI is listed in Spring 2026. In our 2026-09-18 directory snapshot, 112 of 193 listed companies in that cohort have YC’s primary industry label B2B (58.0%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.
Public website snapshot
Observed 2026-09-19T16:16:15.678Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.
| Signal | Homepage observation |
|---|---|
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Not observed in this response |
| Docs/developer link | Not observed in this response |
| Pricing link | Observed |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |
Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.
About the author
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.
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