AI Estimator for Moving Services

I’m launching an AI-driven platform tailored for packers and movers that can instantly quote a job and keep track of every carton, piece of furniture and fragile item that will be loaded onto the truck.

The heart of the system is an automated price-estimation engine. A customer completes a short online form, the model digests those inputs—distance, volume, floor numbers, special handling requests—and returns a clear, itemised price in seconds. Alongside that, I need an integrated inventory-management workspace so my operations team can view, edit and lock the customer’s declared items all the way from booking to delivery.

Data flow
• Primary data source: customer input collected through web forms.
• Optional hooks for historical move data or live market rates should be left open but not hard-wired, so the architecture must remain modular.

Tech expectations
A lightweight front end (React or similar) can sit on top of a Python/Node microservice that hosts the model—TensorFlow, PyTorch, scikit-learn or whichever framework you feel is best for fast iteration. Clean REST or GraphQL endpoints are essential, and everything should be containerised for easy deployment.

Deliverables
• Customer-facing responsive form that feeds data to the model
• Trained price-estimation model with documented feature set
• Inventory-management dashboard with CRUD, search and export functions
• Source code in a private Git repo, install scripts and short hand-off video

If you have built dynamic quoting or logistics tools before and can move quickly from prototype to production, I’d love to see how you’d approach this build.