Every lead researched before a rep opens it
by AGNTOfficialAgent template
New signup or inbound lead? An agent researches the company, scores the fit against your criteria, and writes the enriched record straight into your CRM.
Opens in AGNT and takes about a minute.
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- 5
- Tools connected
- ~10 min
- Setup, 4 steps
- Local
- Runs on your machine
- Per category
- You approve
- Any model
- Uses the one you have
What the agent actually does
Reps open a record that is already briefed
The moment a form is submitted or a trial starts, the agent goes looking: what the company does, roughly how big it is, what stack it appears to run, recent news worth mentioning. The rep opens a record that already has the context they would otherwise have spent fifteen minutes assembling.
Score against your ICP
Fit is judged against criteria you write in plain language — not a points table bolted onto firmographic fields. "Series A or later, technical team, already using a workflow tool" is a description an agent can actually evaluate, including the parts that only show up in prose on a careers page.
CRM stays the source of truth
Findings are written back into HubSpot or Salesforce as structured fields with the reasoning attached, so the enrichment is visible where reps already work rather than in a report nobody opens.
The tools this job needs
HubSpot
Where the work arrives. The CRM your pipeline reporting depends on. The agent watches it and reads what turns up in full, rather than matching a rule against a subject line.
Salesforce
Context the agent pulls in before deciding. The enterprise system of record for revenue. It is read, not just referenced — which is what lets the decision account for it.
Firecrawl
Context the agent pulls in before deciding. Clean page extraction for research-grade scraping. It is read, not just referenced — which is what lets the decision account for it.
Slack
Where the result lands. Team chat where operations actually surface. Nothing is written here until the agent has formed a view and, where you asked for it, you have approved it.
The brief it works from
This is the actual instruction set the template installs — what the agent is told to do, and what it is told never to do. Every line of it is yours to edit in AGNT after install.
Read the full brief
You research inbound leads the moment they arrive, so a rep opens a record that is already briefed.
What to find
Start with the obvious: what the company does, roughly how big it is, what it sells and to whom. Then find the signal that actually predicts fit, which is almost never firmographic. Job postings imply the problems they are hiring to solve. Public documentation reveals their stack. A changelog shows whether they are actively building. A pricing page shows who they sell to. Read those the way a good SDR would.
Score against the user's icp, in their words
They will describe their ideal customer in prose, including the disqualifiers. Evaluate against that description rather than a points table. Then write the reasoning next to the score, specifically enough to be argued with: "strong fit — engineering-led, two automation roles open, docs reference a competitor" is useful. "Score: 8" is not, and will be ignored within a week.
Write back where the rep already works
Structured fields into the CRM, plus a short note with the reasoning. Research that lives in a report nobody opens has no value. Fill empty fields; do not overwrite anything a human entered unless explicitly told you may.
When there is nothing to find
Say so. Mark the record "insufficient public information" and move on. A confidently invented profile is far worse than an empty one — a rep who opens a call having read a fabricated detail loses the deal in the first minute, and loses trust in you permanently.
Cite your sources so any claim can be checked. Speed matters here: inbound interest decays fast, and the whole point is that the research is finished before anyone has looked at the lead.
Never contact the prospect. You prepare; the rep decides and speaks.
Shown exactly as it ships. The agent inherits whichever model you already use.
Why enrichment data alone is not enough
Data vendors return firmographics: headcount, industry code, funding. That tells you the shape of the company and nothing about whether it is a fit for what you sell. The signal that matters is usually qualitative — a job posting implying the problem you solve, a docs page revealing their stack, a changelog showing they are actively building. An agent reads those the way a good SDR would, then records what it found and why it mattered.
Scoring you can argue with
A score with no reasoning is a number people quietly ignore. When the agent writes "strong fit: engineering-led, hiring two automation roles, currently on a competitor mentioned in their public docs", a rep can agree or disagree with a specific claim. That is what makes the score usable rather than decorative — and it is also what lets you correct the criteria when it is consistently wrong about a segment.
Speed changes conversion, not just tidiness
Inbound interest decays fast. An enrichment pass that completes in a minute means the first touch can be same-hour and specific; a nightly batch means it is next-day and generic. Because the agent runs on arrival rather than on a schedule, the research is finished before anybody has looked at the lead.
Common questions
Where does the research come from?
Public sources — the company site, careers pages, docs, changelogs, news — plus any enrichment API you already pay for. Sources are recorded so a rep can check a claim.
What happens when it cannot find anything?
It says so. A record marked "insufficient public information" is useful; a confidently invented profile is worse than an empty one.
Will it overwrite data our reps entered?
Only where you allow it. The usual configuration is that agents fill empty fields and add notes, while human-entered values are left alone.