Automates enrichment from multiple data sources, discovers verified contacts, scores leads, and alerts your team for fast, qualified outreach.
The AI agent accepts a company domain and industry priority from a form, enriches with firmographics, tech stack, and social data, and scores the lead with Gemini AI. It stores the full lead profile in Google Sheets and makes proactive recommendations for outreach. It notifies the team in Slack when a lead scores high to accelerate follow-up.
A quick summary of capabilities across the workflow.
Ingests the domain and priority from the form.
Enriches firmographics, location, tech stack, and social data via Clearbit.
Finds up to five verified email contacts and identifies senior decision-makers via Hunter.io.
Checks Google Maps for rating, reviews, and business status.
Scrapes the homepage to extract phone numbers, hiring signals, pricing pages, and social links.
Scores the lead with Gemini AI, assesses ICP fit, writes a personalized opener, and suggests the next action.
This AI agent reduces manual research time and data gaps by consolidating data sources into one score. It provides clear next actions and an audit trail for each lead.
A simple 3-step flow that non-technical users can follow.
A form collects the domain, industry, and priority, triggering the AI agent workflow.
The agent calls Clearbit and Hunter.io, checks Google Maps, scrapes the site for tech signals and hiring/pricing pages, and runs Gemini AI to score.
Saves the lead to Google Sheets and issues a Slack alert when the score meets the threshold.
A realistic scenario showing time saved and outcomes.
Scenario: A rep submits the domain 'acme.io' with industry 'Software' and priority 'High'. The AI agent enriches the domain with Clearbit firmographics, gathers 5 Hunter.io contacts and identifies top-level decision-makers, checks Google Maps rating and status, scrapes the homepage for phone and pricing, and runs Gemini AI to score 82 with strong ICP fit. It writes 35+ fields to Google Sheets and sends a Slack alert with the complete intelligence report to the outreach squad. Outcome: The rep has ready contacts and a tailored opener, cutting manual research from 15–30 minutes per lead to seconds.
One supporting sentence.
Need fast, accurate lead lists with verified contacts to start conversations.
Require high-quality leads with clear ICP fit and ready-to-use contact details.
Consolidates lead data and scoring for attribution and segmentation.
Need real-time visibility into hot leads and team SLA compliance.
Seek evidence of market demand and partnership opportunities from qualified prospects.
Audit data quality and adjust scoring thresholds over time.
One supporting sentence explaining that the AI agent interacts with tools.
Enriches firmographics, location, tech stack, and social profiles via API.
Finds up to five verified emails and identifies decision-makers.
Fetches rating, review count, and business status.
Extracts phone numbers, tech usage, hiring and pricing signals, and social links.
Scores the lead 0–100, evaluates ICP fit, and writes outreach opener.
Stores 35+ lead fields for pipeline tracking.
Sends real-time alerts when a lead scores above the threshold.
Six practical scenarios where this AI agent adds value.
One supporting sentence with short explanation.
The enrichment sources provide authoritative data, but results depend on the source data quality. The AI agent caches and timestamps data, and you can re-run enrichment on demand. When discrepancies are detected, the system flags them for review. For critical contacts, you should verify in your CRM. Regularly updating credentials and monitoring API limits helps maintain accuracy.
The AI agent processes publicly available business data and user-provided inputs. You should ensure compliance with GDPR, CCPA, and other regional regulations by configuring data retention and access controls. Access is restricted to authorized users, and logs are auditable. Consider internal policies and vendor data processing agreements for full compliance.
Yes. The score threshold is adjustable in the pipeline, and ICP criteria can be updated to reflect your ideal customer profile. You can tune weights across data points like revenue, tech stack, and engagement signals. After adjustments, re-run a sample of leads to validate improvements. Ongoing optimization supports better hit rates.
Enrichment runs in seconds per lead, depending on API call limits and network latency. The design supports batch processing and concurrent lookups to scale to hundreds of leads per day. You can queue leads and monitor throughput in real time. If a source is temporarily unavailable, the workflow continues with fallbacks and retries.
CRMs can be connected via API or middleware. The agent can push complete lead records to your chosen CRM and update statuses based on the score. You can configure field mappings and trigger automations inside your CRM for seamless workflows. Regular syncs prevent data drift and ensure alignment with sales processes.
The workflow is designed to continue when non-critical steps fail, with fallback defaults and clear signals for remediation. Scrape errors are logged, and the system can retry or skip to preserve progress. You’ll receive a summary of any failed steps for quick triage. Critical outcomes, like scoring and storage, are guaranteed unless a fatal error occurs.
Implement periodic re-enrichment and score recalibration as your ICP shifts. The system supports audit trails and versioning of lead records, so you can track changes over time. Regular reviews by your data or sales ops team help maintain accuracy. You can configure data retention policies to align with compliance needs.
Automates enrichment from multiple data sources, discovers verified contacts, scores leads, and alerts your team for fast, qualified outreach.
