Today I completed the second core workflow of my AI Lead Qualification & Sales Automation Platform.
Yesterday I built the Lead Capture Engine.
Today I connected it to the AI Qualification Engine.
Now, every new lead can automatically move from data collection to AI-powered analysis.
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Workflow 01 β Lead Capture Engine
- Multi-source lead intake
- Data validation
- Data normalization
- Supabase storage
- Activity logging
- Production-ready error handling
β¬οΈ Automatically triggers
π€ Workflow 02 β AI Qualification Engine
- Retrieves newly captured lead
- Builds AI-ready context
- Uses AI to analyze the lead
- Extracts buying intent and business insights
- Generates an AI qualification summary
- Updates the lead record
- Creates qualification activity logs
- Gracefully handles AI failures with a pending review process
Instead of stopping when AI fails, the workflow safely marks the lead for manual review, ensuring no opportunities are lost.
π§ Platform Roadmap
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01 β Lead Capture Engine
β
02 β AI Qualification Engine
β³ 03 β AI Lead Scoring Engine
β³ 04 β CRM Sync Engine
β³ 05 β Notification Engine
β³ 06 β Follow-Up Automation Engine
β³ 07 β Analytics & Activity Engine
β³ 08 β AI Sales Assistant
Every workflow is designed as an independent module that can be maintained, upgraded, and reused without affecting the rest of the platform.
The goal isn't just to automate tasksβit's to build a production-ready AI system that manages the entire sales process, from capturing leads to qualifying them, prioritizing opportunities, updating the CRM, notifying the sales team, and automating follow-ups.
Next milestone: AI Lead Scoring Engine.
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