Route scoring, demand prediction, and fleet intelligence. Decisions that compound efficiency.
We build the systems that turn logistics data into operational advantage.
Logistics is a decision machine: which route, which warehouse, which carrier, when to reorder. Most of these decisions are still manual or rule-based. We build AI systems that optimize routes, predict demand, and give you real-time visibility across the supply chain.
Why AI in Logistics is different.
Logistics is the industry where small percentage improvements translate to massive dollar savings. Last-mile delivery accounts for 53% of total shipping costs. Route optimization alone can save 15-25% on fuel and time. Demand forecasting that is 5% more accurate can free up billions in working capital across the supply chain.
The companies deploying AI for route optimization and demand forecasting are seeing 30% faster deliveries and 65% fewer stockouts. The ones running static routes and spreadsheet forecasts are absorbing cost increases they could have avoided.
The complexity is not the algorithm. It is the data. Logistics data lives in TMS, WMS, ERP, carrier APIs, IoT sensors, and weather feeds. Getting that data clean, connected, and flowing in real-time is 80% of the work. The optimization model is the easy part.
The Problems That Slow You Down
Route planning is manual and suboptimal
Dispatchers plan routes based on experience and fixed zones. Dynamic conditions like traffic, weather, and demand shifts aren't factored in.
Demand forecasting misses by 20-30%
Overstock in some warehouses, stockouts in others. The forecast runs on historical averages, not real-time signals.
Last-mile delivery is the cost black hole
Last mile is 50% of shipping cost. Failed deliveries, return trips, and narrow time windows compound the problem.
Supply chain visibility is 48 hours behind
You find out about delays after they've already cascaded. No real-time tracking, no predictive ETAs, no exception alerting.
Systems for Logistics
Route Optimization AI
Dynamic routing that factors in traffic, weather, delivery windows, and vehicle capacity, recalculating in real-time.
View service →Demand Forecasting
ML models that predict demand by SKU, location, and time window using sales data, seasonal patterns, and external signals.
View service →Supply Chain Visibility
Real-time dashboards tracking shipments, inventory, and exceptions across the entire supply chain.
View service →Fleet Management Apps
Driver apps, dispatch dashboards, and customer tracking, mobile-first, offline-capable, GPS-integrated.
View service →These aren't pitch deck scenarios. Every use case maps to a system pattern we've built and deployed in production.
What We Build in Logistics
Network Demand Forecasting
VP Supply Chain5-15% excess inventory, frequent OTIF misses; spreadsheet-driven forecasts siloed by region.
Hierarchical XGBoost/LSTM on orders, POS, promotions, weather, events, with an optimization layer for replenishment by SKU-location.
Dynamic Route Optimization
Head of TransportationStatic routing tools; 10-30% extra miles, missed delivery windows, fuel overspend.
ML + ILP solver on orders, fleet constraints, traffic, service levels, with continuous re-optimization and predictive ETA.
Warehouse Pallet Intelligence
VP OperationsManual counting causes 2-5%+ inventory errors, congestion, safety incidents, high labor costs.
Vision-guided robots with CNN pallet detection + SLAM navigation, demand-forecast restocking into WMS.
Cross-Border Documentation Agent
Head of Global LogisticsHours per shipment copying data across BOL/invoices/customs; discrepancies trigger inspections, five-figure penalties per container.
LLM agent ingests BOL/invoices/packing lists, reconciles fields, validates HS codes, submits customs forms via API/RPA.
Logistics Document Processing
VP Operations3PLs manually key thousands of BOL/POD/rate confirmations. 1-3 day lags, billing errors.
GenAI doc pipeline reads scanned docs, extracts references/quantities/accessorials, validates against shipments, pushes to TMS/ERP.
Fleet Predictive Maintenance
Head of Fleet OperationsVehicle breakdowns cause missed deliveries, emergency repairs, under-utilization.
Time-series on telematics/sensors for failure prediction and service scheduling into fleet maintenance systems.
Carrier Performance Analytics
VP LogisticsSLA breaches, damage, invoice errors persist unchecked. No granular carrier scoring.
ML on TMS/ERP/service data, producing carrier KPI scores by route/region, trend detection, and LLM executive summaries.
Control Tower Exceptions Agent
Head of Control TowerControl towers drown in tracking feeds/EDI; exceptions discovered late, fire-drills, poor CX.
LLM+event-stream agent flags anomalies (missed scans, dwell, ETA drift), proposes mitigation, drafts customer notifications.
Building the system is half the job. Growing the business around it is the other half.
How We Grow Logistics Brands
AEO for TMS Software Queries
Head of MarketingLogistics firms miss 52% of "best TMS software" to ChatGPT; zero-clicks reduce demos 33%.
Schema feature matrices, ROI calcs, Perplexity tracking to trial funnels.
LinkedIn Ads for Procurement Leads
Demand Gen DirectorLinkedIn CPL $85-130 for ops tools; under 9% SQL.
Supply chain VP targeting, case studies, HubSpot scoring/nurture.
HubSpot Lead Scoring for TMS Demos
Marketing Ops Lead2.5K leads/quarter; 65% unqualified.
HubSpot workflows (ROI tools, visits), sequences, CRM sync.
How We Work With Logistics
AI Systems & Agents
LLMs, agent chains, and intelligent workflows, wired into your ops, not sitting in a sandbox.
Learn more →Machine Learning Solutions
Prediction systems that run 24/7. Not proof-of-concepts gathering dust.
Learn more →Data Engineering & Analytics
Your data is scattered across 15 tools. We wire it into one system that answers questions.
Learn more →Mobile App Development
iOS, Android, and web applications, shipped fast, built to last.
Learn more →Frequently asked questions
Typically 15-25% reduction in fuel and time costs. The savings come from fewer miles, less idle time, and better load utilization, not faster driving.
Yes. Oracle TMS, SAP TM, Blue Yonder, and custom systems. We build integration layers, not replacements.
Cold-start problem. We use analog products, category trends, and marketing signals to forecast until the product builds its own history.
AI moves fast. Stay ahead.
No spam. One actionable email per week on AI systems and growth.
Every late delivery is a decision that could have been made earlier.
Start with a logistics data assessment. We'll identify where AI delivers the fastest cost savings.