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Lead scoring

Qualify an inbound sales lead from raw form text.

Live toolRun this on your own data with the Lead Scorer →

Try it live

This is the real thing, not a mockup. Edit the input, hit Run, and Jev returns every typed answer in one round trip — free, no signup. Now picture the same call fired across thousands of items in parallel.

POST jevtypesafeai.com/api/v1/decide
state — the input software gives Jev297c
questions — the typed decisions you want back
scorefit
How strong a fit is this lead for a technical B2B infrastructure product?
→ 0…4 · 5 levels
choiceroute
Where should this lead be routed?
→ one of: enterprise, smb, nurture, disqualify
noulbuying_now
Is this lead actively in a buying cycle right now?
→ probability 0.0 … 1.0
real API · free · no signup
Typed, calibrated output appears here.
Pick a demo, tweak the input, and hit Run Jev.
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The decisions Jev makes

In a single call, Jev evaluates each of these — in parallel, against the same input:

scorefit

How strong a fit is this lead for a technical B2B infrastructure product?

rates it on an ordered scale:

  1. poor fit / tire-kicker
  2. weak fit
  3. decent fit
  4. strong fit
  5. ideal, high-intent buyer
choiceroute

Where should this lead be routed?

picks one of these options:

  • enterprise — enterprise account executive
  • smb — self-serve / SMB
  • nurture — marketing nurture sequence
  • disqualify — not a fit, disqualify
noulbuying_now

Is this lead actively in a buying cycle right now?

returns a calibrated yes/no probability.

The exact request

This is the real payload behind the live demo — copy it, change the state, and you're building:

{
  "model": "jev-latest",
  "state": "Inbound demo request. Name: Priya Nadkarni. Company: Northwind Robotics (~450 employees). Role: VP of Engineering. Message: 'We're replacing a homegrown rules engine that routes millions of events a day and evaluating vendors this quarter. Need something we can pilot in 2 weeks. Budget approved.'",
  "questions": {
    "fit": {
      "type": "score",
      "instructions": "How strong a fit is this lead for a technical B2B infrastructure product?",
      "criteria": [
        "poor fit / tire-kicker",
        "weak fit",
        "decent fit",
        "strong fit",
        "ideal, high-intent buyer"
      ]
    },
    "route": {
      "type": "choice",
      "instructions": "Where should this lead be routed?",
      "criteria": {
        "enterprise": "enterprise account executive",
        "smb": "self-serve / SMB",
        "nurture": "marketing nurture sequence",
        "disqualify": "not a fit, disqualify"
      }
    },
    "buying_now": {
      "type": "noul",
      "instructions": "Is this lead actively in a buying cycle right now?"
    }
  }
}

Wire it into your code

Read the typed answers and branch in plain code — no parsing. Auto-handle the high-confidence cases and route the uncertain ones to a bigger model or a human. It's one API call and output is free, so ask every question you need at once.

Build your own

Every scenario above is a single API call. Try any of them free in the playground, then get a hosted key to ship it in minutes.

Run this demo ▶Get an API key →
Lead scoring — a Jev use case with a live demo · Jev by TypeSafe AI