Lead generation is one of those tasks everyone knows they should automate… but most teams still do it manually.
Every week the process looks something like this:
🔎 Search LinkedIn for companies
🌐 Visit dozens of websites
👤 Find the CTO, VP, or Director
📧 Hunt for contact information
✍️ Write personalized outreach emails
⏳ Lose half a day doing repetitive work
What if all of that happened automatically?
What if you woke up Monday morning to find:
✅ A list of companies matching your ICP
✅ Decision makers already identified
✅ Company research already completed
✅ Lead qualification scores calculated
✅ Personalized outreach drafts ready to send
That’s exactly what I built using Hermes Agent.
Full Video Walkthrough:
🤖 The Goal
I wanted a system where I could provide a simple campaign brief and have a team of AI agents handle the entire lead generation workflow.
Something like:
“Find SaaS startups with 10-200 employees that build AI developer tools. Identify decision makers and prepare personalized outreach.”
Instead of manually managing every step, a multi-agent workflow handles the process from start to finish.
🏗️ Architecture Overview
The pipeline consists of six specialized AI agents:
🎯 Orchestrator Agent
Acts like a sales manager.
Responsibilities:
- Creates execution plans
- Creates tasks
- Assigns work to specialist agents
- Tracks progress
- Manages dependencies
- Controls workflow phases
🔍 Prospector Agent
Finds companies that match your ICP.
Input:
- Keywords
- Industry
- Company size
- Target market
Output:
- Qualified company list
Example keywords:
- AI Developer Tools
- LLM Infrastructure
- DevOps Automation
- AI Engineering Platforms
🌐 Scraper Agent
Researches every company discovered during prospecting.
Collects:
- Products
- Services
- Company descriptions
- Locations
- Social profiles
- Technology signals
All data gets enriched and stored automatically.
👥 Contact Finder Agent
Identifies the right people inside each company.
Targets:
- CTOs
- VPs
- Directors
- Founders
Then gathers available contact information from multiple sources.
✉️ Outreach Agent
Generates personalized outreach emails.
Instead of generic templates, it references:
- Company initiatives
- Product offerings
- Technology stack
- Industry positioning
Result:
Much more relevant outreach messages.
📊 Analyst Agent
Scores every lead against the Ideal Customer Profile (ICP).
Evaluation criteria:
- Company size
- Industry fit
- Product relevance
- Buying potential
- Strategic alignment
Each company receives a qualification score between 0 and 1.
This helps prioritize outreach efforts.
🧠 Why Multi-Agent Systems Work So Well
Most people try to build lead generation using a single AI agent.
The problem?
One agent becomes responsible for:
- Research
- Scraping
- Qualification
- Personalization
- Coordination
That quickly becomes messy.
Instead, I use specialist agents.
Each agent focuses on one responsibility only.
Benefits:
✅ Better task quality
✅ Easier debugging
✅ Better scalability
✅ Parallel execution
✅ Cleaner workflows
📋 Workflow State Machine
The workflow runs in phases:
Campaign Brief
│
▼
Prospecting
│
▼
Research & Enrichment
│
▼
Contact Discovery
│
▼
Outreach Generation
│
▼
Lead Qualification
│
▼
Campaign Report
The orchestrator only unlocks the next phase once the previous phase is completed successfully.
This prevents bad downstream data from contaminating later stages.
🗂️ Hermes KANBAN Board = Shared Agent Memory
One of my favorite parts of Hermes Agent is its Kanban workflow system.
The Kanban board acts as a shared coordination layer between agents.
Every agent can:
📖 Read task status
✍️ Update progress
🔄 Create follow-up tasks
🚦 Track dependencies
The orchestrator uses the board to understand:
- What is complete
- What is blocked
- What should happen next
This creates a surprisingly robust autonomous workflow.
⚡ Running a Campaign
To launch a campaign I simply provide:
Product
What I’m selling
ICP
Who I want to target
Discovery Keywords
Where prospecting should begin
Goal
What outcome I want
Example:
Run a full B2B lead generation campaign for ShipMe Agent, an AI agent for QA and DevOps automation.
ICP: AI SaaS startups, 10-200 employees.
Keywords: AI Developer Tools, LLM DevOps Automation.
Goal: 10 ranked qualified leads with decision-maker contacts and personalized outreach emails drafted
The orchestrator takes over from there.
📈 End Result
At the end of a run I receive all information organized in CSV files:
Companies
- ICP matched companies
- Enriched company data
Contacts
- Decision makers
- Contact information
Outreach
- Personalized email drafts
Qualification
- Lead scoring
- Prioritized opportunities
Report
- Campaign summary
- Workflow results
All generated automatically from a single task.
🔥 Real Value
The biggest win isn’t saving a few minutes.
It’s eliminating repetitive work entirely.
Instead of spending hours every week:
❌ Searching
❌ Researching
❌ Copy-pasting
❌ Writing first drafts
I can focus on:
✅ Sales conversations
✅ Closing deals
✅ Improving campaigns
✅ Building relationships
The AI team handles the operational work.
🛠️ Resources
🔗 Agents SOUL.md files & Custom Hermes Skills: https://github.com/vivekshetye/hermes-lead-generation-pipeline
💬 What Would You Automate?
If you had a team of AI agents working for you 24/7, what business workflow would you automate first?
Lead generation?
Customer support?
Market research?
Content creation?
I’d love to hear what you’re building.
Top comments (1)
🚀 Multi-agent lead generation is one of the most practical AI workflows I’ve built so far.
What other business workflows would you automate with Hermes Agent?
👇 Drop your ideas below lead generation, market research, customer support, content creation, or something else?