Lead generation, built for Marketing Teams.
BeReach reads the public signals your target accounts leave, like funding, hiring, launches and reviews. It qualifies each one against your ICP, then hands you named contacts and a warm, contextual reason to reach out for every campaign.
| # | Name | Conn | Signal |
|---|---|---|---|
| 1 | Helena Voss VP Marketing · Calyx | 2nd | Launched product |
| 2 | Omar Haddad Demand Gen · Verano | 2nd | Raised Series C |
| 3 | Lena Fischer Head of Growth · Stelo | 3rd | Launched product |
| 4 | Theo Almeida CMO · Ridge | 2nd | New category |
| 5 | Yara Khoury Marketing Lead · Nook | 3rd | Rebranded |
To a qualified list
any campaign, any segment
Typical acceptance rate
warm, contextual first touch
Typical reply rate
vs generic cold outreach
Accounts scored to ICP
every list matches the play
Your agent scans where these accounts actually show up: funding and launch data, reviews and traction, tech stacks, hiring posts, and the people behind them.
Every account is scored against your ideal profile on size, stage, traction and buying signals, so noise is filtered out before it ever reaches you.
For each qualified account, the agent finds the right decision-maker and helps you send a contextual message that references a real signal, not a generic template.
Build the account list for a campaign from live signals like funding, hiring and launches, not a database snapshot. Your spend lands on companies showing intent right now instead of names that went cold months ago.
Every account is scored against the same ICP your reps sell to and comes with named contacts. Marketing and sales work one target list, so campaigns and outreach reinforce each other instead of chasing different accounts.
The Reacher drafts a contextual opener for each account, so a campaign can pair broad reach with a warm, multichannel first touch that references a real signal instead of a generic template.
Because it reads the open web in real time, you can rebuild a target list the moment a new signal appears. Campaigns stay tied to who is in-market this week, not who was six months ago.
BeReach reads the public web in real time, across funding, hiring, launches, reviews, tech stacks and public profiles, then cross-references them to build ABM lists that fit your ICP with named contacts and a reason to reach out. You aim campaigns at accounts showing intent right now instead of a static database snapshot.
A bought list has no timing and goes stale the day you get it. BeReach surfaces accounts showing live signals, scores each against your ICP, and attaches the context, so campaigns land on in-market accounts and your budget stops funding reach on companies that will never buy.
Yes. Every account is built from public signals across the open web, cross-referenced and verified. There is no scraping behind a login and no private database, which is why the lists stay tied to who is in-market rather than a quarterly refresh.
Yes. After the Finder surfaces accounts and the Qualifier scores them, the Reacher drafts a warm, multichannel opener that references a real signal, so a play can pair broad reach with a personal first touch to named buyers.
Yes. Just describe the campaign fit, like accounts that raised recently and would suit a new webinar, and the agent handles the combination of stage, size and intent 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 contacts ready for the campaign.

The all-in-one AI SDR was supposed to replace your sales team. By early 2026, most companies that tried it have gone back to hybrid models. Here's what AI agents actually do well for LinkedIn prospecting - and where the hype still outpaces reality.
Alexandre Sarfati

Companies doing LinkedIn ABM well generate $10+ in pipeline per dollar spent and 44% higher ROAS than Google. But most ABM on LinkedIn fails because teams treat it like targeted cold outreach. Here's what the data shows actually works.
Alexandre Sarfati

Belkins analyzed over 20 million LinkedIn outreach attempts across 13,000 accounts. Here's what the data says about cold versus warm approaches, which combinations work, and what most teams get wrong.
Alexandre Sarfati
Describe your ICP and campaign and let your agents build a signal-based target list with named contacts to warm up.
Free credits inside · no credit card
Click a button and let your favorite AI weigh in.