Custom AI Logistics Systems
Syntora is an AI development agency that specializes in delivering custom logistics solutions for small and mid-sized businesses. We partner with companies to engineer custom route optimization, load matching, and demand forecasting systems tailored to their specific operational constraints.
Syntora is an AI development agency specializing in custom logistics solutions. We design and build systems for route optimization, load matching, and demand forecasting based on your specific operational data and constraints. Our approach focuses on technical architecture and engineering engagements.
Our work focuses on businesses that use a TMS or WMS but need advanced automation for their unique processes. We do not offer off-the-shelf software. Instead, we design and build production-ready systems from the ground up for critical business functions, requiring dedicated engineering expertise.
A typical engagement for a system like route optimization often begins with a discovery phase lasting 2-4 weeks. During this time, we would work closely with your team to understand your operational data, existing workflows, and specific business rules. Your team would provide access to historical shipment data, facility layouts, and operational policies, which are crucial for defining the problem precisely. This initial phase helps define the project scope, deliverables, and estimated build timeline, which can range from 8-16 weeks depending on complexity.
What Problem Does This Solve?
Most small logistics companies start by planning routes in their TMS or with spreadsheets. A 20-person 3PL with four dispatchers spends the first 3 hours of every day manually assigning 30 trucks to loads. This process cannot account for real-time traffic or dynamic Hours of Service (HOS) rules. A single accident on a major highway invalidates the entire plan, forcing drivers to call dispatch for new instructions.
Many TMS platforms offer an 'optimization module' for an extra $150 per user per month. These modules are often just point-to-point distance calculators. They cannot handle multi-stop routes with tight delivery time windows or balance workload fairly across a fleet. The generated routes are often 10-15% less efficient than what an experienced dispatcher can build manually.
Third-party routing tools are designed for last-mile parcel delivery, not regional freight. They don't model a 53-foot trailer's turning radius or factor in fixed dock appointment times. A route that appears optimal on their map is often physically impossible for the truck, resulting in refused deliveries, wasted fuel, and service failures.
How Would Syntora Approach This?
Syntora's approach to building custom logistics AI systems begins with a deep dive into your operational data. We would start by auditing your existing WMS and TMS to understand data availability and API access. Our engineers would then process historical shipment data, typically 6-12 months, using Python and the Pandas library. This analysis identifies operational patterns, such as consistent delays at specific receiving facilities or common routing inefficiencies, which inform the design of optimization models.
For route planning, we would engineer a vehicle routing problem (VRP) solver using Google's OR-Tools library. The system would be designed to incorporate your specific business constraints, including driver hours of service, vehicle capacity, customer time windows, and known road restrictions. This solver would evaluate multiple route combinations to identify a near-optimal plan for your fleet based on predefined objectives like minimizing distance or cost. The goal is to provide a significantly improved routing capability compared to manual methods.
The optimization engine would be deployed as a FastAPI service on a serverless platform like AWS Lambda. This architecture allows for on-demand execution, where a webhook from your TMS could trigger the system when a dispatcher requests a new plan. The resulting optimized route would be returned as a structured data object and integrated back into your TMS. We've built similar data processing and API integration pipelines for clients in financial services using Claude API for document analysis, and this established pattern applies directly to logistics data flows.
For demand forecasting, we would develop a predictive model using techniques such as LightGBM. This model would be trained on historical order data, typically 12-24 months, to predict future shipment volumes per lane. The purpose is to provide more accurate forecasts, enabling proactive carrier booking and helping to reduce reliance on the volatile spot market. Our deliverables would include the deployed system, documentation, and a knowledge transfer session to ensure your team can manage and evolve the solution.
What Are the Key Benefits?
Your Daily Routes Planned in 90 Seconds
Stop spending hours building manual routes. The system generates a full day's plan for 30 drivers, accounting for HOS and time windows, in less time than it takes to make coffee.
Pay for the Build, Not Per Dispatcher
A one-time project fee and minimal monthly hosting on your AWS account. No recurring SaaS license that penalizes you for growing your dispatch and operations team.
The Source Code Lives in Your GitHub
You receive the complete Python codebase and deployment scripts. This is your asset, not a black box rental. You can modify or extend it with any developer in the future.
Get Alerts Before a Route Fails
We configure CloudWatch alarms to monitor API latency and error rates. If the solver fails, you get a Slack notification instantly, not a phone call from an idle driver.
Connects Directly to Your Existing TMS
We build direct API integrations with your current Transportation Management System or WMS. There is no new software for your dispatchers to learn.
What Does the Process Look Like?
Week 1: System and Data Access
You provide read-only API credentials for your TMS and WMS. We receive 12 months of historical shipping data and document your exact operational constraints.
Weeks 2-3: Core Engine Development
We build the optimization engine and test it against your historical data. You receive a validation report showing how the model's routes compare to past human-planned routes.
Week 4: Integration and Deployment
We deploy the system on your AWS account and connect it to your live TMS. You get a private staging environment to test route generation with your dispatch team.
Weeks 5-8: Monitoring and Handoff
We monitor the live system for performance and accuracy. At the end of the period, you receive a full runbook with architectural diagrams and maintenance procedures.
Frequently Asked Questions
- How much does a custom logistics system cost?
- Pricing depends on the number of systems to integrate and the complexity of your business rules. A route optimization project for a single depot with under 50 vehicles is a different scope than a multi-state load matching platform. We provide a fixed-price proposal after a 45-minute discovery call where we map out your exact requirements.
- What happens if the AWS service goes down?
- The system is deployed across multiple AWS availability zones for redundancy. If a zone-wide outage occurs, API requests will fail over automatically. For a full region outage, which is extremely rare, the system would be down. The project runbook includes a manual fallback plan so your dispatchers can operate without the tool.
- How is this better than buying routing software like Samsara?
- Samsara provides excellent fleet telematics, but their routing is a generic add-on. We build solutions for your specific business logic. We can build a model that prioritizes loads for your most profitable customers or routes drivers to avoid specific low-clearance bridges, which off-the-shelf software cannot do.
- We use an old, custom-built TMS. Can you integrate with it?
- If your TMS has a documented REST or SOAP API, we can integrate. If it has no API but can export CSV files to an S3 bucket, we can build a batch processing workflow. We've previously integrated with systems over 15 years old using these methods. The key is a reliable way to get data in and out.
- Who handles the monthly cloud hosting bill?
- The system is deployed in your own AWS account. You pay the bill directly to Amazon, which is typically under $50 per month for most SMB workloads. This gives you full ownership and transparency. We help you set up the account and billing alerts during deployment so there are no surprises.
- What performance improvements can we realistically expect?
- Clients typically see a 10-15% reduction in total miles driven and a 20% reduction in planning time. For a 30-truck fleet, this can translate to thousands of dollars in fuel savings per month. The exact improvement depends on the inefficiency of your current process, which we quantify in the initial data audit.
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