AI Inbound Lead Qualification & VIP Routing Gate

id: ai-lead-qualification-and-routing
namespace: company.sales

description: |
  Autonomous inbound lead qualification and sales routing pipeline.
  Ingests new form signups via webhook, enriches company firmographics
  using Google Gemini and Tavily live search, scores Ideal Customer Profile
  (ICP) fit, and instantly routes high-value enterprise leads to VIP Slack channels.

triggers:
  - id: weekly_lead_audit
    type: io.kestra.plugin.core.trigger.Schedule
    description: Weekly sweep to re-evaluate unprocessed or disputed leads. Shipped
      disabled by default.
    cron: "0 8 * * 1"
    disabled: true

  - id: inbound_lead_webhook
    type: io.kestra.plugin.core.trigger.Webhook
    description: Authenticated webhook endpoint triggered by website signup forms or
      CRM integrations.
    key: "{{ secret('WEBHOOK_KEY') }}"

inputs:
  - id: lead_email
    type: STRING
    defaults: sarah.connor@acmecorp.com
    description: Email address of the inbound prospect.

  - id: company_name
    type: STRING
    defaults: Acme Cloud Solutions
    description: Name of the organization submitting the inquiry.

  - id: company_domain
    type: STRING
    defaults: acmecorp.com
    description: Primary web domain used for firmographic enrichment.

  - id: use_case_description
    type: STRING
    defaults: We need to orchestrate mission-critical financial pipelines across 4
      cloud providers and manage 500 daily batch jobs.
    description: Raw problem statement or use case submitted by the user.

  - id: self_reported_team_size
    type: STRING
    defaults: "250-1000"
    description: Team size range selected on the signup form.

tasks:
  - id: enrich_and_score_lead
    type: io.kestra.plugin.ai.agent.AIAgent
    description: Queries live web sources to retrieve company funding and headcount,
      then scores ICP fit and buying intent.
    provider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
      modelName: gemini-2.5-flash
    configuration:
      temperature: 0.1
      maxToken: 4096
      responseFormat:
        type: JSON
        jsonSchema:
          type: object
          required:
            - company_name
            - qualification_tier
            - icp_fit_score
            - key_intent_signals
            - recommended_sales_angle
            - executive_briefing
          properties:
            company_name:
              type: string
            qualification_tier:
              type: string
              enum:
                - ENTERPRISE
                - MID_MARKET
                - SMB
                - DISQUALIFIED
            icp_fit_score:
              type: integer
              description: Score from 0 to 100 based on tech stack fit, scale, and buying
                intent.
            key_intent_signals:
              type: array
              items:
                type: string
            recommended_sales_angle:
              type: string
            executive_briefing:
              type: string
    contentRetrievers:
      - type: io.kestra.plugin.ai.retriever.TavilyWebSearch
        apiKey: "{{ secret('TAVILY_API_KEY') }}"
        maxResults: 3
    systemMessage: |
      You are an expert Enterprise Sales Development and RevOps Director.
      Your job is to evaluate inbound leads for an enterprise workflow orchestration platform.

      Scoring Criteria:
      - ENTERPRISE (Score 80-100): Over 250 employees, multi-cloud or complex infrastructure, explicit high-scale volume (>100 daily jobs), high buying intent.
      - MID_MARKET (Score 50-79): 50-249 employees, growing data stack, moderate automation needs.
      - SMB (Score 20-49): Under 50 employees, single-cloud, simple cron replacement.
      - DISQUALIFIED (Score 0-19): Personal email providers (gmail, yahoo), spam, student projects, or completely irrelevant inquiries.

      Always verify the company domain via web search to confirm legitimate operating status and headcount.
    prompt: |
      Evaluate the following inbound prospect:
      - Lead Email: {{ inputs.lead_email }}
      - Company Name: {{ inputs.company_name }}
      - Domain: {{ inputs.company_domain }}
      - Self-Reported Team Size: {{ inputs.self_reported_team_size }}
      - Stated Use Case: {{ inputs.use_case_description }}

      Search the company web presence, determine their tech footprint, calculate their ICP fit score, and return the structured qualification payload.

  - id: parse_qualification_metrics
    type: io.kestra.plugin.scripts.python.Script
    description: Extracts qualification tier and generates a structured sales battle-card.
    taskRunner:
      type: io.kestra.plugin.core.runner.Process
    inputFiles:
      qualification.json: "{{ outputs.enrich_and_score_lead.textOutput }}"
    outputFiles:
      - sales-battle-card.md
    script: |
      import json
      from kestra import Kestra

      with open("qualification.json", "r", encoding="utf-8") as f:
          data = json.load(f)

      company = data.get("company_name", "Unknown")
      tier = data.get("qualification_tier", "SMB")
      score = data.get("icp_fit_score", 0)
      signals = data.get("key_intent_signals", [])
      angle = data.get("recommended_sales_angle", "Standard product demo.")
      briefing = data.get("executive_briefing", "")

      # Write executive battle card
      card = f"""# Inbound Lead Battle Card: {company}
      **Qualification Tier:** {tier} | **ICP Fit Score:** {score}/100

      ## Executive Summary
      {briefing}

      ## Key Buying Intent Signals
      """ + "\n".join([f"- {s}" for s in signals]) + f"""

      ## Recommended Sales Outreach Angle
      {angle}
      """

      with open("sales-battle-card.md", "w", encoding="utf-8") as out:
          out.write(card.strip())

      print(f"Lead processed: {company} -> Tier: {tier} (Score: {score})")

      Kestra.outputs({
          "qualification_tier": tier,
          "icp_fit_score": score,
          "company": company,
          "angle": angle[:150]
      })

  - id: routing_gate
    type: io.kestra.plugin.core.flow.If
    description: Routes enterprise-tier leads immediately to VIP sales channels
      while sending SMB leads to nurture queues.
    condition: "{{ outputs.parse_qualification_metrics.vars.qualification_tier ==
      'ENTERPRISE' or outputs.parse_qualification_metrics.vars.icp_fit_score >=
      80 }}"
    then:
      - id: alert_vip_sales_channel
        type: io.kestra.plugin.slack.notifications.SlackIncomingWebhook
        description: Alerts senior account executives on high-value inbound enterprise
          leads.
        url: "{{ secret('SLACK_WEBHOOK_URL') }}"
        payload: |
          {
            "channel": "#sales-enterprise-inbound",
            "text": "🔥 *VIP Enterprise Inbound Lead Detected: {{ inputs.company_name }}* 🔥\n\n*ICP Fit Score:* `{{ outputs.parse_qualification_metrics.vars.icp_fit_score }}/100`\n*Prospect:* `{{ inputs.lead_email }}`\n*Team Size:* `{{ inputs.self_reported_team_size }}`\n\n*Recommended Outreach Angle:*\n{{ outputs.parse_qualification_metrics.vars.angle }}\n\nReview the full battle card in Kestra execution `{{ execution.id }}`."
          }
    else:
      - id: log_standard_nurture
        type: io.kestra.plugin.core.log.Log
        description: Records standard or SMB lead to standard self-service nurture queue.
        message: "Lead for {{ inputs.company_name }} classified as {{
          outputs.parse_qualification_metrics.vars.qualification_tier }} (Score:
          {{ outputs.parse_qualification_metrics.vars.icp_fit_score }}). Routed
          to automated email nurture track."

errors:
  - id: alert_on_failure
    type: io.kestra.plugin.slack.notifications.SlackIncomingWebhook
    description: Alerts technical operations if lead qualification fails.
    url: "{{ secret('SLACK_WEBHOOK_URL') }}"
    payload: |
      {
        "channel": "#revops-alerts",
        "text": "❌ *Lead Qualification Pipeline Failed* ❌\nWorkflow `{{ flow.id }}` failed on prospect `{{ inputs.lead_email }}` (Execution `{{ execution.id }}`)."
      }

Inbound signup forms often force sales teams into an uncomfortable trade-off: either ask prospects 15 friction-heavy qualification questions and crush conversion rates, or collect basic emails and waste hours manually researching companies on LinkedIn and Google. Slow responses to high-value enterprise leads directly reduce close rates.

This blueprint deploys an autonomous lead qualification agent using Kestra, Google Gemini, and Tavily web retrieval. As soon as an inquiry arrives via webhook, the pipeline searches company firmographics, verifies team size and cloud footprint, calculates an objective ICP fit score (0 to 100), and creates an executive sales battle card. High-intent enterprise prospects immediately trigger an urgent Slack alert with a personalized outreach angle, while lower-tier inquiries route to automated nurture.

How it works

enrich_and_score_lead (io.kestra.plugin.ai.agent.AIAgent) searches the company domain via TavilyWebSearch, extracts headcount and infrastructure scale, and generates an objective qualification score using a strict JSON schema.
parse_qualification_metrics (io.kestra.plugin.scripts.python.Script) formats key intent signals into an executive sales-battle-card.md artifact stored on the execution.
routing_gate (io.kestra.plugin.core.flow.If) evaluates the calculated score. Enterprise accounts trigger an instant notification to #sales-enterprise-inbound, while standard leads route to automated self-service email campaigns.

What you get

Sub-minute lead qualification without forcing prospects through long multi-page forms.
Tailored sales battle cards containing company context and suggested pitch angles.
Zero human triage overhead for personal or low-intent email signups.

Who it's for

RevOps, Sales Engineering, and Growth Marketing teams at B2B SaaS companies.
Account Executives seeking immediate alerts when high-value buyers submit inquiries.

Why orchestrate this with Kestra

Lead routing requires orchestrating external search APIs, LLM inference, and notification platforms reliably. With Kestra, webhook ingestion triggers instantly with zero cold-start delay, secret management protects your search and CRM credentials, and every lead qualification has an immutable execution log for attribution modeling.

Prerequisites

A Google Gemini API key.
A Tavily API key for web search firmographic retrieval.
A Slack incoming webhook endpoint for sales team notifications.

Secrets

GEMINI_API_KEY: API key for Google Gemini provider.
TAVILY_API_KEY: API key for Tavily search retriever.
SLACK_WEBHOOK_URL: Slack incoming webhook URL for sales alerts.
WEBHOOK_KEY: Authentication key for webhook trigger security.

Quick start

Configure the GEMINI_API_KEY, TAVILY_API_KEY, SLACK_WEBHOOK_URL, and WEBHOOK_KEY secrets in your Kestra namespace.
Send a test webhook payload with your prospect details or run a manual execution.
Inspect the generated sales-battle-card.md in the execution output artifacts.
Enable the webhook trigger and connect it to your website form handler (e.g., HubSpot, Marketo, or Typeform).

How to extend

Add an HTTP task to push qualified enterprise accounts directly into Salesforce or HubSpot.
Add a Loop task (io.kestra.plugin.core.flow.Loop) to backfill and re-score historical CRM lead exports.

AI Inbound Lead Enrichment, Scoring and VIP Routing Gate

How it works

What you get

Who it's for

Why orchestrate this with Kestra

Prerequisites

Secrets

Quick start

How to extend

Links

Tasks

Orchestrate with Kestra

Share this Blueprint

Create a Blueprint

New to Kestra?

AI Inbound Lead Enrichment, Scoring and VIP Routing Gate

How it works

What you get

Who it's for

Why orchestrate this with Kestra

Prerequisites

Secrets

Quick start

How to extend

Links

Tasks

Orchestrate with Kestra

Share this Blueprint

Create a Blueprint

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