AI Inside Sales Assistant – Development Plan

Posted by Frank on July 21, 2025
Posted in: Uncategorized.

Goal

Automate all repetitive sales rep tasks for Frank Bredow, starting with Cascadia Clip opportunities in Colorado and Utah, and later expanding to more products, regions, and reps. The system must learn from user corrections to improve over time.

Segmented Build Plan

Segment 1 – Core Interface + Lead Discovery

Purpose: Create the base system to manage products, scan construction databases, and flag opportunities.

Developer Requirements:

  1. Admin Interface
    • Add/remove product lines.
    • Store product descriptions, standard email text, brochures/PDFs.
    • Link products to their keywords for database scanning.
  2. Database Connection Module
    • Screen construction databases for keywords (from product list).
    • When a keyword match is found, download relevant specs, drawings, and project info.
    • Store files in a structured project folder (naming convention: ProjectName_Date).
  3. Review & Approval Workflow
    • Display all discovered opportunities for manual review.
    • If approved by user: push project data to Pipedrive via API.
    • If rejected: log reason for rejection (for machine learning feedback loop).

End State of Segment 1:
Frank can manage products, scan for matches, download project docs, and approve/reject projects directly into Pipedrive.

Segment 2 – Substitution Request Automation

Purpose: Automatically fill and send substitution request forms to GCs.

Developer Requirements:

  1. Form Template Library
    • Store AIA substitution request forms (PDF/DOC) by GC.
    • Map fields to data pulled from the approved project record.
  2. Form Fill Module
    • Auto-populate substitution form fields with project data + product info.
    • Allow user to make edits before submission.
  3. Submission Workflow
    • Send form via email to GC contact (from project record in Pipedrive).
    • Log sent forms in project record with date/time.

End State of Segment 2:
Frank approves a project ? AI fills the correct substitution form ? AI sends it to GC ? logs action in Pipedrive.

Segment 3 – Approval Tracking + Installer Outreach

Purpose: Track substitution approvals and start installer/roofer engagement.

Developer Requirements:

  1. Approval Tracking
    • Monitor GC responses to substitution requests.
    • Flag approval/denial in Pipedrive.
  2. Installer Outreach Automation
    • Upon approval ? automatically identify potential installers/roofers in project region.
    • Generate outreach emails using stored templates + project details.
    • Log installer communications in Pipedrive.

End State of Segment 3:
Once substitution is approved, AI starts reaching out to qualified installers automatically.

Segment 4 – Quote Process Automation

Purpose: Manage quotes from request to follow-up.

Developer Requirements:

  1. Quote Request Intake
    • Auto-detect quote requests from email inbox.
    • Link request to existing project in Pipedrive or create new one.
  2. Quote Tracking
    • Log sent quotes.
    • Schedule follow-ups (1 week, 1 month, 2 months after bid date).
  3. Follow-Up Automation
    • Send pre-approved follow-up emails from stored templates.
    • Alert user if phone follow-up is required.

End State of Segment 4:
Quotes are logged, follow-ups happen automatically, and Frank is alerted only when human contact is needed.

Segment 5 – Learning & Optimization

Purpose: Make the AI smarter over time.

Developer Requirements:

  1. Correction Feedback Loop
    • Whenever Frank changes a keyword, rejects a project, or edits an email, store that action for retraining.
  2. Performance Tracking
    • Measure success rate of substitution approvals, quote wins, and follow-ups.
    • Adjust scanning priorities and outreach patterns based on data.
  3. Scalability Layer
    • Allow additional products, reps, and regions without re-coding core modules.

End State of Segment 5:
The AI self-optimizes to reduce false positives, improve targeting, and handle more sales coverage with less human input.

Why This Segmentation Matters

  • Lower Startup Cost: Only Segment 1 needs to be built first to start delivering value.
  • Faster Iterations: Each segment can be tested and deployed independently.
  • Scalable Design: Adding new products or regions won’t require redoing core functions.
  • Continuous Learning: AI gets better the more Frank uses it.