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USE CASESAI LEAD QUALIFICATION

Company dataAI agents · RevOps · Sales

Help your agent explain account fit

Give your qualification agent company data and a clear definition of a good-fit account. Use rules for the decision and your agent for a readable explanation, with a review path when the data is incomplete.

100 free credits / month. No card. No sales call.

Enriched data → your next action
Start withInbound lead → acme.example
EnrichLoops adds profile data
Industry
Software
Employees
240
HQ country
Canada

Matches software, 200–500 employees, Canada → agent explains account fit

Illustrative data and rules. Your workflow controls the action.

WHEN TO USE IT

Teams building an inbound qualification assistant with defined account criteria and a review process for uncertain results.

WHAT IT ENABLES

Produce an account-fit decision with an explanation tied to explicit criteria and returned fields.

How the workflow works

Enrich a company, evaluate your explicit fit criteria, then ask your agent to explain the decision from the available evidence.

  1. 01

    Define the criteria

    Specify supported industries, employee bands, and countries in a rule set your team can review.

  2. 02

    Evaluate enriched fields

    Wait for the completed company profile, then evaluate each criterion as matched, unmatched, or unknown.

  3. 03

    Explain and review

    Have your agent explain the evaluation. Route incomplete or uncertain records to your team’s review queue.

IMPLEMENTATION GUIDE

Use rules for repeatable decisions

Encode numerical thresholds and supported values in your own workflow rather than asking a language model to invent them. Keep each criterion’s result and input field. Your agent can summarize why an account matches, but the decision should be reproducible from the same profile and rule version.

Keep unknown separate from no

If headcount or geography is missing, mark that criterion unknown. Do not let an agent replace the absent value with an estimate. Require review for incomplete evaluations and combine fit with first-party intent only when your team has defined how to use that signal.

Connect the result to a controlled action

Use a backend tool to submit enrichment and retrieve the completed task. Treat profile text as data, validate the agent’s explanation against your evaluation, and let your CRM workflow control assignments. Keep the criteria and freshness timestamps with the result so the team can audit the decision later.

Connect the workflow

Use the API overview for request and task handling, or the Loop guide for webhook delivery.

Company enrichmentSee the company fields your qualification rules can use.

Common questions

Is AI qualification a built-in EnrichLoops feature?

This is a workflow you build using EnrichLoops company data. Your rules evaluate fit, your agent explains the result, and your CRM or application performs the next action.

Can enriched data establish buying intent?

Firmographic data describes company fit. Use your own engagement or buying signals to evaluate intent and keep that evidence distinct from company attributes.

Put this workflow to work

Start with 100 free credits every month. Test with your own data.

Get your free API key