AI Automation lead generation that finds decision-makers.
BeReach reads the public signals AI and automation companies leave, like funding rounds, model and product launches, GitHub stars and hiring for ML and applied AI roles. It qualifies each account against your ICP, then helps you reach the right person with a warm, contextual message.
1,000+ teams4.9| # | Name | Conn | Signal |
|---|---|---|---|
| 1 |  Marcus Reeve CEO · Nuvex AI | 2nd | Liked the post |
| 2 |  Sofia Almeida VP Product · Latimr | 2nd | Commented |
| 3 |  Ravi Chandran Head of ML · Corvex | 3rd | Commented |
| 4 | Hannah Berg Founder · Automaton | 2nd | Reposted |
| 5 | Tobias Kraus GTM Lead · Halden | 3rd | Liked the post |
Public signal sources
funding, launches, repos, hiring
Typical acceptance rate
warm, contextual first touch
Typical reply rate
vs generic cold outreach
To a qualified list
any stage, any AI niche
Your agent tracks the places AI companies leave a trail: seed and Series A rounds, model and agent launches, star velocity on public repos, and open ML, applied AI and DevRel roles.
Each company is scored against your ideal profile on stage, funding recency, repo traction and team shape, so pre-product experiments drop out before they reach your list.
For every account that clears the bar, the agent surfaces the Head of ML or the founder still writing code, then drafts a message about the launch or round it actually saw. You approve each one before it sends.
Know exactly when an AI company raises, who led it, and how much. A freshly funded team is scaling compute, tooling and headcount, so you can reach them while the budget is fresh and the roadmap is being set.
New model releases, agent launches and Product Hunt debuts show which teams are shipping right now. Use launch signals to time outreach at the exact moment a company is proving traction and hunting for what comes next.
Star velocity and active repositories reveal which open-source AI projects are gaining real adoption. Lead with a reason tied to their momentum, not a cold pitch to a name you pulled from a static list.
An AI team posting ML, applied AI or DevRel roles is scaling fast. Track hiring to find companies in active build mode, the ones most likely to invest in new infrastructure and partnerships.
Prefer to work in Claude?
BeReach runs as a connector inside Claude and Claude Cowork. Ask in plain language and it prospects, qualifies, and drafts your outreach, with every send waiting for your approval. See the Claude connector.
BeReach reads the public web in real time, across funding data, model and product launches, GitHub, job boards and public profiles, then cross-references them to surface qualified AI accounts along with the actual decision-maker's name and how to reach them. It's live signal, not a quarterly database dump.
Legacy databases index established firmographics and refresh slowly, so the newest AI startups, open-source projects and applied AI teams are under-covered or missing entirely. BeReach searches the real-time sources where these companies actually announce themselves, like funding rounds, model releases and GitHub activity, so it finds accounts those databases don't have.
Yes. Every lead is built from public signals across the open web, cross-referenced and verified. There's no scraping behind a login and no private database, which is exactly why the coverage of fast-moving AI and automation companies is so much better.
Funding stage and recency, headcount and growth, model and product launch activity, GitHub traction, and hiring for ML and applied AI roles. You describe your ICP in plain language and the agent scores each account against it, so only the strong-fit ones reach you.
Yes, and that's the difference from a list tool. After the Finder surfaces accounts and the Qualifier scores them, the Reacher helps you open a warm, multichannel conversation with the right person, referencing a real signal like a recent raise or model launch instead of a generic template.
Yes. Just describe what you want, like a seed applied AI startup hiring ML engineers with a repo over 3,000 stars, and the agent handles the combination of stage, role, launch and GitHub signals. No filters or boolean syntax to learn.
Usually under two minutes. Describe the accounts you want, the agent scans the public sources, qualifies them against your ICP, and returns a list with named decision-makers ready to reach out to.
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Describe your ideal AI account and let your agent find, qualify, and reach the decision-makers behind it.
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