Use case
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Inbound SDR
AI lead scoring built on your closed-won deals
Nex runs AI lead scoring against the patterns in your own closed-won deals, not a generic MQL point sheet. Every score comes with its reasons and the source records behind them.
The problem
Most lead scoring models are a points table someone built once: plus ten for a job title, plus five for a pricing page visit. Nobody remembers why the weights are what they are, and they drift away from the deals you actually close. Reps stop trusting the score, sales and marketing argue about MQLs, and good leads wait in a queue while a high score on a bad fit gets the first call.
How the agent does it
Ingest the new lead. The agent picks up a new inbound lead, or an existing lead that gains material new context.
Resolve person and company. It matches the lead to the right person and company using your CRM, communication and workspace context in Nex.
Compare with closed-won evidence. It checks the lead against the patterns in deals you have already won, alongside your ICP and current company context.
Score with reasons. It produces a score with the reasoning and the source records behind it, so anyone can see why a lead ranked where it did.
Route for review or follow-up. It routes the lead by the thresholds your team defines, and holds outreach and record changes for approval.
What you get
A score for each inbound lead, based on your closed-won patterns
The reasons and evidence behind every score
Linked Nex records and proposed CRM updates, ready to approve
A routing decision or next action for the lead owner
Works with
CRM
Email and communication
Calendar
Questions
What is AI lead scoring?
AI lead scoring ranks leads by how closely they resemble the customers you already won, instead of adding up fixed points for titles and clicks. Nex compares each lead with your closed-won evidence and current context, then explains the score so a person can check it.
How is this different from a predictive lead scoring model?
Like a predictive lead scoring model, it learns from your outcomes. The difference is that every score arrives with its reasons and source records, and your team sets the routing thresholds, so the model is something you can inspect rather than a number you have to trust.
Will it change records or contact leads on its own?
No. Scoring and reasoning run without sign-off, but consequential outreach and record changes wait for approval from the owner you assign.
How do I get started?
Click Deploy, connect your CRM and the tools the agent reads, and set who reviews its work. You start free with some free AI usage, and plans are $49/month after that, refundable within 7 days.
Hire this agent and see its first result today
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