AI B2B Prospecting
Agent Jesse crawls the live internet in real time to find high-intent companies and decision-makers, then enriches them with verified contact data. Everyone can buy the same 40,000 companies — what's scarce is knowing which of them is worth an email this week.
B2B prospecting software helps sales teams find and research the companies and decision-makers worth contacting. Almost every tool in the category does some version of three jobs: identify companies matching a profile, identify the right people inside them, and supply verified contact details.
Where tools differ is where they look. Most search a stored database — records collected in advance and refreshed on a schedule. Agent Jesse searches the live web at the moment you ask, which means it can surface a company because of something that happened this morning. That difference is the whole product.
Buy a database, filter to your ICP, export, sequence. It works until it doesn't — for three structural reasons rather than any fixable one.
Databases are built from periodic scrapes and user uploads. Titles go stale, people leave, companies pivot. You find out through bounce rates — and bounced sends cost you domain reputation, which is far more expensive than the subscription.
"Series A SaaS, 50–200 employees, US" returns the same companies for you as for the three competitors running the same filter on the same database. Same names, same inboxes, same week.
"Uses HubSpot" is a state. "Posted three RevOps roles last week and named a HubSpot migration in the job description" is a moment. The first is in the database. The second is on a careers page, and a filter cannot reach it.
Most teams respond by buying more data. But the constraint isn't volume — it's that nothing in the list tells you who to email first.
No boolean strings, no filter stacking. "Series A B2B SaaS companies that just hired their first sales engineer" is a valid query.
Funding announcements, job postings, conference exhibitor lists, product launches, press coverage, permit filings, hiring pages — read at query time. A round announced this morning can be on your list this afternoon.
You see why each company surfaced before you write a word. That's your opening line — the difference between a personalised email and a mail-merged one.
50+ enrichment points per record, including verified contact data for the decision-makers who actually matter to your deal.
Push to your CRM or sequencer. Set daily alerts, and new companies matching the same ICP arrive automatically as their signals fire.
Every one of these is a single plain-English query.
“Companies that raised a Series A in the last 60 days.”
New budget, new headcount, new problems. You arrive during the buying window instead of two quarters after it closed.
“Companies hiring RevOps or Sales Ops roles this month.”
A company hiring for a problem has admitted, in public, that it has the problem. The job description is often better discovery than a discovery call.
“Companies whose job posts mention [competitor tool].”
Documented pain, in the company's own words, timestamped.
“Exhibitors at [conference] in the [category] track.”
Sponsor and exhibitor lists publish weeks early and are pure ICP concentrate. You reach out before the badge-scan flood, not during it.
“Companies that launched a new product in the last 30 days.”
A team that just shipped is a team scaling something.
“Territory and account lists from live sources.”
Because the input is the live web rather than a shared database, two teams running similar ICPs surface genuinely different accounts.
Live-web prospecting at scale
Verified email deliverability
Enrichment points per record
Teams prospecting with Agent Jesse
We wrote up the full category, competitors included, in Best B2B Lead Generation Tools in 2026.
Describe your ideal customer in one sentence. Get companies showing real buying signals, enriched with verified contacts, in minutes.
AI B2B prospecting uses AI to find and qualify prospective customers rather than relying on manual research or static filters. In practice this means two things: interpreting a plain-language description of your ideal customer instead of requiring boolean filters, and reading unstructured public sources — job posts, funding news, event listings — that a structured database cannot represent.
A contact database answers "which companies match this profile" from records gathered in advance. AI prospecting on the live web answers "which companies are doing something relevant right now" by searching current sources at query time. The first optimises for coverage, the second for timing.
Yes, and this is the main practical reason to use one. Newly founded companies, companies that just raised, and companies whose relevant signal is a job post or a conference listing frequently have no useful database record. Because Agent Jesse reads live public sources rather than a stored index, it can surface them.
Agent Jesse enriches every company across 50+ points and verifies contact data before it reaches your list. As a rule, treat any vendor's accuracy claim as a hypothesis and test it: run one real list, sequence it, and look at your bounce rate. That's the only number that matters, and it's the reason the free plan exists.
Yes. Lists export for use in your existing CRM and outbound sequencing tools, and daily alerts push new matching companies as their signals appear.
Minutes. You describe your ICP in a sentence rather than configuring filters, so the first list is a single query — which is also why evaluating it is cheap.