← All use cases

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 api.typesafe.ai/v1/systemone
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.
Get an API key →← All use cases

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