The Client
A growing solar energy company with a nationwide sales force and a rapidly expanding customer base. The company had accumulated over 30,000 quotes worth of historical data but was still relying on a manual quoting process that slowed down sales reps and created inconsistencies across the organization.
The Project
VisionWrights recognized the client's historical quote dataset as the foundation for a machine learning solution that could automate and accelerate the entire quoting workflow. We built a production-ready ML API that generates optimized solar panel layouts in approximately 5 seconds — trained on the full corpus of historical data.
The model was integrated directly into the sales workflow, allowing reps to generate accurate, data-driven panel configurations on-site during customer consultations. The solution accounts for roof dimensions, shading patterns, and regional installation requirements to produce layouts that are both technically sound and commercially optimized.
The Result
The deployment fundamentally changed how the sales team operates. Quote generation time dropped from minutes of manual configuration to seconds of automated output. Consistency improved across the entire organization — every rep now produces layouts built on the same data-driven logic.
- ✓Production-ready ML API deployed to the sales team
- ✓Quote generation time reduced from minutes to approximately 5 seconds
- ✓Consistent, data-driven panel layouts across all reps and regions
- ✓Sales reps freed to focus on customer conversations and closing deals
- ✓Model trained on 30,000+ historical quotes for high accuracy