Today I finished the foundation of my AI Lead Qualification & Sales Automation platform.
Instead of building one giant workflow, I'm designing the system as multiple independent workflows that each handle one responsibility.
That makes it easier to:
- Debug
- Scale
- Maintain
- Reuse across future client projects
Today's completed workflow:
โ
01 โ Lead Capture Engine
Features:
โข Accepts leads from websites, Facebook Ads, Google Ads, LinkedIn, Voice Agents, Chatbots & APIs
โข Normalizes different payloads into one standard schema
โข Validates required fields
โข Stores everything in Supabase
โข Creates activity logs automatically
โข Includes production-ready error handling and structured API responses
Database architecture is also complete, making it easy to plug in future AI modules.
The full system roadmap
โ
01 โ Lead Capture
โณ 02 โ Validate Lead
โณ 03 โ Save Lead
โณ 04 โ AI Qualification
โณ 05 โ Lead Scoring
โณ 06 โ CRM Update
โณ 07 โ Notifications
โณ 08 โ Automated Follow-Ups
When all eight workflows are connected together, the result will be an AI system that captures, qualifies, scores, updates the CRM, notifies the team, and follows up with leads automatically.
No manual data entry.
No leads slipping through the cracks.
๐ฐ Pricing
If I were building this Lead Capture Engine as a standalone production workflow for a client, I'd likely price it around $500โ$1,000, depending on integrations, validation rules, and deployment requirements.
The complete AI Lead Qualification & Sales Automation platform would typically be a much larger project, potentially in the $3,000โ$8,000+ range depending on customization and ongoing support.
Still a lot more to build, but the foundation is officially in place.
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