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AI lead qualification + CRM automation — interactive preview

Pick a sample on the left. Watch the workflow run. Inspect the structured output. This is a mock — real builds adapt to your tools and data.

Pick a sample lead

Raw lead

Edit the message to see how the qualification adapts in a real implementation. (Sample run uses pre-computed output.)

From
Sara Whitaker · VP of Operations
Company
Northbound Logistics · 400 employees
Region
North America
Captured
Pricing page form · Today, 09:14

Pipeline

Each step is mocked with a fixed delay so you can see the shape of the workflow.

  1. 01
    Capture & normalize
    Parse the raw message, extract sender, company, and intent keywords.
  2. 02
    Enrich with company data
    Pull employee count, vertical, funding, and tech stack from public sources.
  3. 03
    Score against your ICP
    LLM applies your fit, intent, urgency, budget, and authority rules.
  4. 04
    Route, draft, and log
    Assign owner, write CRM fields, draft a tailored reply, start SLA timer.

Qualification result

Run the workflow to reveal the AI's structured output.

Press Qualify lead to score, route, draft a CRM record, and write a follow-up email.

Where this writes back

  • HubSpot
  • Salesforce
  • Attio
  • Pipedrive
  • Gmail
  • Slack
  • Clearbit

Real builds write to whatever CRM, inbox, and chat your team already runs in. The list above is illustrative.

Mock preview. Sample qualifications are pre-computed — editing the message body does not re-run a real model. Production builds adapt your ICP rules, tone, routing logic, and CRM schema.

Adapt this qualification flow to your CRM

The preview above uses sample leads and mock automation. A real implementation can connect to HubSpot, Pipedrive, Salesforce, Airtable, Slack, email, and your existing qualification rules so your team only spends time on the leads most likely to become revenue.