jev·agent

← All use cases

Use case · Mixed

Lead scoring and qualification with Jev

Score fit and intent against your own rubric, and route the hot ones to a human immediately rather than in tomorrow's batch.

The problem

Lead qualification is usually a nightly batch job or a rules engine nobody has updated in two years. Doing it with an LLM per lead is affordable but too slow to act on in-session.

How Jev handles it

Score fit and urgency against rubrics built from your actual sales criteria, plus Noul checks for disqualifiers. Fast enough to act on before the prospect leaves.

python
response = client.system_one(
    model="jev-latest",
    state=f"{form_submission}\n\nCOMPANY: {enrichment_data}",
    questions={
        "fit": Score(
            instructions="How well does this lead match our ideal customer?",
            criteria=["Poor", "Marginal", "Good", "Ideal"],
        ),
        "intent": Score(
            instructions="How far along is this buyer?",
            criteria=["Browsing", "Researching", "Evaluating", "Ready to buy"],
        ),
        "competitor": Noul(
            instructions="Is this a competitor rather than a prospect?",
            criteria=NoulCriteria(true="Works at a competing vendor",
                                  false="Genuine prospect"),
        ),
    },
)

a = response.answers
if a["fit"].score == "Ideal" and a["competitor"].noul < 0.2:
    page_sales_immediately()

Notes from the field