Automate Your Last Mile Delivery Operations

Many e-commerce SMBs start by planning routes with Google Maps or a basic Shopify plugin. This involves manually exporting orders into a spreadsheet, copy-pasting addresses, and trying to sequence them logically. The process is slow, error-prone, and creates static routes that cannot account for traffic, delivery windows, or vehicle capacity.

Off-the-shelf tools like Onfleet or Routific offer a step up but introduce their own constraints. Their per-driver pricing models become expensive for businesses with fluctuating seasonal demand. More importantly, their optimization algorithms are black boxes. They cannot incorporate your specific business logic, like prioritizing high-value customers or batching deliveries to a specific neighborhood on a designated day. You are forced to fit your operations into their software.

Consider a small furniture company with five drivers delivering 40 orders a day. The operations manager spends the first 90 minutes every morning exporting a Shopify CSV and manually building routes. When a new order arrives at 10 AM, they must call a driver, ask for their location, and mentally calculate if the new stop is feasible. This manual intervention delays all subsequent deliveries and makes scaling impossible without hiring more planners.

The structural problem is that these tools are closed platforms. They cannot pull real-time inventory status from your warehouse management system (WMS) or react to a customer service ticket. They treat route planning as an isolated task, separate from the rest of your operation. A business-critical logistics system needs to be deeply integrated, not a siloed third-party application.

The engagement would begin with an audit of your current last mile process. Syntora maps the flow of an order from your e-commerce platform to the final proof-of-delivery. We would analyze 3 months of historical order data to understand delivery density, time windows, and common exception types. You receive a scope document detailing the proposed data connections and the logic for the routing model.

The system would be a Python-based service using the FastAPI framework, deployed on AWS Lambda for cost-effective, event-driven processing. When an order is marked 'ready for delivery' in Shopify, a webhook triggers the service. The service would use a routing engine like Google's OR-Tools, feeding it address data, vehicle capacities, and your specific business constraints. For parsing unstructured customer delivery notes, the Claude API can extract key details like 'leave with doorman' or 'call 10 minutes before arrival', achieving a response time under 500ms per route calculation.

The final deliverable is a custom API that your existing systems call to get an optimized route plan. A simple web interface, built and deployed on Vercel, provides a dashboard for the operations manager to view driver locations and manage exceptions. You receive the full source code in your GitHub repository and a runbook explaining how to manage the system.