Lead Generation · Sales & Marketing Teams

AI Agent for Discover and Enrich Decision-Makers with Apollo

Automate discovery, enrichment, and verification of decision-makers to deliver ready-to-contact leads.

How it works
1 Step
Step 1: Discover decision-makers
2 Step
Step 2: Enrich and centralize
3 Step
Step 3: Verify and report
Query Apollo Organization Search and People Search to identify C-suite and VP-level contacts for target accounts.

Overview

End-to-end lead discovery, enrichment, verification, and reporting.

The AI agent scans target companies, identifies key decision-makers, and enriches their contact details with LinkedIn profiles, emails, and phone numbers. Then it routes records requiring review to Slack for human verification, ensuring accuracy and compliance. Finally, it updates Google Sheets across Companies, Contacts, and Contacts (Verified) and delivers a weekly summary of newly verified leads.


Capabilities

What Discover and Enrich Decision-Makers AI Agent does

Automates end-to-end lead discovery, enrichment, and verification.

01

Identify target decision-makers using Apollo Organization Search and People Search.

02

Enrich profiles with LinkedIn URLs, emails, and phone numbers via Apollo enrichment APIs.

03

Update the Google Sheets tabs: Companies, Contacts, and Contacts (Verified).

04

Flag records needing human verification and notify via Slack.

05

Verify data with human checks and move verified contacts to Contacts (Verified).

06

Generate and deliver weekly summaries of newly verified leads to Slack.

Why you should use Discover and Enrich Decision-Makers AI Agent

Before: teams struggle with incomplete data, scattered sources, and slow lead validation. After: the AI agent automates discovery and enrichment, adds verified contacts to a centralized sheet, and delivers weekly summaries of new leads.

Before
Data is scattered across Apollo, LinkedIn, and emails, causing inconsistent lead lists.
Decision-maker roles are hard to identify accurately without manual research.
Enrichment data (LinkedIn, emails, phone numbers) is incomplete or outdated.
Verification is manual and slow, delaying outreach.
Leads database drifts due to lag in updates and verification.
After
Centralized, up-to-date leads in Google Sheets.
Verified decision-maker contacts with enriched data.
Automated weekly summaries of newly verified leads.
Slack prompts for verification ensure data quality.
Faster outreach with ready-to-contact leads.
Process

How it works

A simple 3-step flow that non-technical teams can follow.

Step 01

Step 1: Discover decision-makers

Query Apollo Organization Search and People Search to identify C-suite and VP-level contacts for target accounts.

Step 02

Step 2: Enrich and centralize

Enrich with LinkedIn profiles, emails, and phone numbers via Apollo APIs and write results to the Google Sheets.

Step 03

Step 3: Verify and report

Route uncertain records to Slack for human verification, update Contacts (Verified) when approved, and send weekly summaries.


Example

Example workflow

A practical scenario showing end-to-end automation.

A new company is added to the Companies tab. The AI agent runs a discovery pass, returns 3 decision-makers (CEO, CTO, VP of IT) with LinkedIn profiles and emails, and writes them to Contacts. It flags 1 record for verification; Slack sends a verification prompt. After human confirmation, 2 contacts are marked as Verified in Contacts (Verified). A weekly summary of the newly verified leads is posted to Slack.

Lead Generation Google SheetsSlackApollo APILLM Service (OpenAI) AI Agent flow

Audience

Who can benefit

Roles that rely on accurate, enriched lead data.

✍️ Sales managers

Need reliable lead lists to plan and execute outreach campaigns.

💼 Business development reps

Require faster access to decision-maker contacts for outreach.

🧠 Marketing operations

Need enriched profiles for ABM targeting and attribution.

Sales operations

Maintain a clean, deduplicated leads database.

🎯 Growth teams

Prefer weekly verified-lead summaries for pipeline planning.

📋 Data compliance officers

Need traceable data verification workflows and auditability.

Integrations

Connects to Google Sheets, Slack, Apollo, and an LLM service.

Google Sheets

Reads and writes to the Companies, Contacts, and Contacts (Verified) tabs; triggers Pending when Domain changes.

Slack

Sends verification prompts and weekly reports to a designated channel.

Apollo API

Provides Organization Search, Organization Enrichment, People Search, and Bulk People Enrichment during discovery and enrichment.

LLM Service (OpenAI)

Generates company summaries and infers departments based on job titles during enrichment.

Applications

Best use cases

Practical scenarios to drive outreach and data quality.

Discovery of decision-makers for new target accounts
Enrichment of contact data with LinkedIn profiles and direct contact details
Weekly verification and reporting of new leads
Maintenance of a clean, deduplicated leads database
ABM campaigns with enriched, verified target lists
Onboarding and handoff for sales teams with ready-to-contact records

FAQ

FAQ

Common questions about setup, data quality, and workflow.

The agent uses Apollo Organization Search and People Search to locate senior decision-makers based on company size and industry. It enriches results with LinkedIn profiles, emails, and phone numbers, and uses heuristics to filter out non-decision-makers. Duplicates are de-duplicated during logging, and flagged records are routed for review. You can adjust target roles and rules in the workflow settings.

Yes. You can define target roles and seniority levels in Apollo and adjust enrichment and categorization rules in the workflow. The system supports department inference from job titles to improve segmentation. You can also apply domain filters to reduce irrelevant results. Changes take effect on subsequent discovery runs.

Records with uncertain data are sent to Slack for human verification. Verified contacts are moved to the Contacts (Verified) tab, and an audit trail is maintained. Verification results feed into weekly Slack reports for visibility. You can designate verifiers and set SLAs for review.

Requests are queued and retried with back-off to respect rate limits. Priority accounts are processed first, and a throttle notification is posted to Slack if limits affect throughput. The workflow resumes automatically once limits reset, ensuring eventual completion without data loss. You can adjust rate limits in API configurations.

Data is stored in Google Sheets with access controls and transmitted over secure channels during API calls. Edits and verifications are logged with timestamps for auditability. You can configure retention and access policies to meet compliance needs. Regular reviews of permissions are recommended.

Yes. A test mode can simulate the end-to-end flow using a sandbox sheet and dummy accounts. You can verify discovery, enrichment, and verification without touching live data. After successful testing, migrate to the live sheet and notify the team via Slack. The test mode prevents unintended data changes.

Prepare a Google Sheet template with the required tabs and columns, obtain API keys for Apollo and the LLM service, and configure a Slack channel for prompts and reports. Import the workflow into your n8n instance and reference your sheet and channel. Ensure proper permissions and run a controlled test before going live.


AI Agent for Discover and Enrich Decision-Makers with Apollo

Automate discovery, enrichment, and verification of decision-makers to deliver ready-to-contact leads.

Use this template → Read the docs