Industries
Data and AI Solutions for Logistics
Optimize routes, networks and warehouses, predict arrival times accurately, give customers real-time visibility and digitize freight data with AI and connected platforms.
Move Goods Smarter with Connected Logistics Data
Carriers, freight forwarders, third-party logistics providers, parcel and last-mile operators and shippers run networks in which every hour and every kilometer matters. Volatile demand, capacity swings, port congestion, labor shortages and rising customer expectations for precise delivery windows make planning harder each year. Meanwhile, regulations such as the EU eFTI Regulation on electronic freight transport information and new emissions reporting requirements are pushing the sector toward digital, structured data. Logistics companies that use data well cut cost and win customers.
Hanoi Technology builds the data platforms, optimization engines and AI applications behind modern logistics. We integrate TMS, WMS, telematics and partner data into real-time visibility platforms, build ETA prediction and route and network optimization, apply computer vision and document AI to warehouse and freight processes and calculate shipment-level emissions using recognized methodologies such as the GLEC Framework and ISO 14083.
The Challenge
The Data Challenges Facing Logistics Companies
Logistics networks depend on data from many parties, and much of it arrives late, incomplete or on paper.
Fragmented Partner and Shipment Data
A single shipment can involve shippers, forwarders, carriers, terminals, customs brokers and last-mile providers, each with its own systems and formats. Building an accurate, timely picture of where goods are requires integrating many feeds of uneven quality.
Unreliable ETAs and Exceptions
Static schedules and carrier estimates rarely reflect traffic, weather, dwell times or port congestion. Customers and planners discover delays too late to react, and service teams spend hours answering where-is-my-shipment requests.
Inefficient Routes, Loads and Networks
Manual or rule-based planning leaves trucks partially loaded, routes suboptimal and network flows unbalanced. Fuel, labor and empty miles add up quickly across large fleets.
Paper Documents and Emerging Digital Rules
Bills of lading, CMRs, customs declarations and delivery proofs are still often handled on paper or as PDFs. Requirements for digital freight information and shipment-level emissions reporting demand structured, trustworthy data.
Business Value
What Modern Data and AI Deliver for Logistics
Accurate, Dynamic ETAs
Machine learning predicts arrival times using live location, traffic, weather and historical performance. Customers and planners trust delivery windows.
Lower Transport Costs
Route, load and network optimization reduce kilometers driven, empty runs and overtime. More shipments move with the same assets.
Real-Time End-to-End Visibility
A single view of shipments across modes and partners, with proactive exception alerts. Service teams resolve issues before customers call.
More Productive Warehouses
Slotting, labor planning and pick path optimization raise throughput. Computer vision and IoT reduce manual counting and damage.
Faster Document Processing
Document AI extracts data from freight, customs and delivery documents. Billing cycles shorten and data is ready for digital reporting.
Measurable Emissions Reduction
Shipment-level emissions calculations support customer reporting and help identify lower-carbon modes and routes.
Logistics Is an Optimization Problem at Scale
Every day a logistics network solves millions of small decisions about which vehicle, which route, which slot and which partner. The difference between a good and a great operator comes from making those decisions with better data and better algorithms, consistently. We help logistics companies build that advantage.
Our Services
Our Logistics Solutions
Six solution areas covering transport, warehousing, visibility and compliance.
Logistics Data Platform and Integration
We integrate TMS, WMS, ERP, telematics, carrier APIs, EDI and partner feeds into a cloud data platform with a common shipment and event model.
- Shipment and event data model
- EDI, API and telematics integration
- Data quality monitoring for partner feeds
Shipment Visibility and Control Tower
We build real-time visibility platforms with milestone tracking, exception management and customer-facing tracking portals.
- Control tower dashboards
- Exception detection and alerting
- Customer tracking portal and APIs
ETA Prediction and Exception Management
We develop machine learning models that predict arrival times and delay risks across road, sea, air and last-mile legs.
- ETA prediction models
- Delay risk scoring
- Proactive customer notifications
Route, Load and Network Optimization
We apply mathematical optimization and AI to vehicle routing, load building, dispatch and network design.
- Vehicle routing and dispatch optimization
- Load and container planning
- Network and hub location modeling
Warehouse Analytics and Automation
We optimize slotting, labor planning and picking, and apply IoT and computer vision to inventory counting, damage detection and dock management.
- Slotting and pick path optimization
- Labor demand forecasting
- Vision-based inventory and damage detection
Document AI, Digital Freight Data and Emissions
We digitize freight and customs documents, structure data for electronic freight information exchange and calculate shipment-level emissions with recognized methodologies.
- Document extraction for bills of lading and CMRs
- eFTI-ready structured freight data
- GLEC and ISO 14083 emissions calculation
Explore
Services for Logistics
- Shipment MonitoringReal-time tracking of location and condition.Learn more
- AI Planning and OptimizationRouting, loading and network optimization.Learn more
- IoTConnected fleets, containers and warehouses.Learn more
- Machine LearningETA, demand and delay prediction.Learn more
- HyperautomationAutomate document-heavy freight processes.Learn more
- Sustainability and ESGShipment emissions and decarbonization data.Learn more
Our Approach
How We Engage with Logistics Companies
An operations-first approach that proves value on real lanes, depots and warehouses.
- 01
Operations and Data Assessment
We review the network, processes, systems and partner data relevant to the initiative, with operations, commercial and IT teams.
Deliverables: Process and data assessment · Opportunity sizing
- 02
Use Case and KPI Definition
We define the target decisions and KPIs, such as cost per drop, on-time performance or ETA accuracy, and select pilot lanes, depots or sites.
Deliverables: Use case charter · Baseline KPIs
- 03
Integrate and Model the Network
We connect required data sources, build the shipment and network data model and set up pipelines with quality checks for partner data.
Deliverables: Integrated data sets · Network and event data model
- 04
Build, Simulate and Pilot
We develop models and optimization engines, simulate them on historical data and then pilot them with planners and dispatchers in live operations.
Deliverables: Simulation results · Live pilot report
- 05
Roll Out and Optimize
We integrate solutions with TMS, WMS and customer channels, roll them out across the network and monitor performance and adoption continuously.
Deliverables: Production integration · Performance monitoring and tuning
Use Cases
Logistics Use Cases
Concrete scenarios for carriers, forwarders, 3PLs and shippers.
Dynamic Last-Mile Routing
Delivery routes are re-optimized each morning and during the day based on new orders, traffic and driver availability. Drivers complete more stops per shift with fewer failed deliveries.
Ocean Freight ETA Prediction
Vessel positions, port congestion and historical dwell times feed a model that predicts container availability. Importers plan inland transport and warehouse labor more accurately.
Control Tower for a 3PL
A unified dashboard shows every customer shipment across carriers with exception alerts. Account managers notify customers of delays proactively rather than reacting to complaints.
Warehouse Labor Forecasting
Inbound and outbound volume forecasts by hour drive shift planning in each warehouse. Overtime and idle time both fall as staffing matches workload.
Freight Document Digitization
Document AI reads bills of lading, delivery notes and invoices and populates the TMS automatically. Billing errors fall and freight data becomes available for digital exchange with authorities and partners.
Shipment-Level Carbon Reporting
Emissions are calculated for each shipment based on mode, distance, load and vehicle data. Shippers receive accurate carbon reports and can compare lower-emission options.
Technology
Platforms and Standards We Work With in Logistics
We integrate with logistics systems and build on open standards and proven optimization tools.
- GS1 EPCIS
- EDI (EDIFACT and X12)
- DCSA Standards
- eFTI
- GLEC Framework
- ISO 14083
- Google OR-Tools
- Gurobi
- TMS and WMS integrations
- Telematics APIs
- Apache Kafka
- Databricks
- Snowflake
- Azure
- AWS
- Power BI
Platforms
Deliver Logistics on Your Preferred Platform
- Microsoft AzureModernize data, analytics and AI within your Azure tenant.Explore
- AWSBuild, migrate and run data and AI workloads on Amazon Web Services.Explore
- Google CloudBigQuery, Looker and Vertex AI for data-driven organizations.Explore
- DatabricksUnified lakehouse for data engineering, analytics and AI.Explore
- SnowflakeElastic cloud data platform for analytics and data sharing.Explore
Why Hanoi Technology
Why Organizations Choose Hanoi Technology
Senior, Cross-Functional Teams
Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.
Proven Delivery
More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.
Radical Transparency
A written update every week and a demo of working software every sprint, so you always know where things stand.
Cost-Effective Global Delivery
Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.
Success Story · Logistics
Route optimization and fleet visibility for a regional logistics company
A regional delivery company handling thousands of shipments a day was planning routes and dispatching by hand. We built dynamic route optimization, a fleet dashboard and a driver app.
Read the Full StoryMore Success Stories
Food delivery
+58%total ordersAI dispatch and live tracking for a food delivery startup
A fast-growing urban food delivery startup was losing customers to slow deliveries at peak times. We built AI order dispatching and connected restaurants, drivers and customers in real time.
Resources
Featured Resources
Industry trends and practical guidance to help you get more value from data, AI and technology.
FSMA 204 After the Delay: Using Shipment Monitoring to Get Traceability-Ready by 2028
The FDA Food Traceability Rule deadline moved to July 2028, but the data work is large. Here is how to use shipment monitoring and event data to get ready without wasting the extra time.
CSRD After the Omnibus: What the Revised ESRS Mean for Reporting From 2027
The Omnibus and the simplified ESRS reshaped EU sustainability reporting in 2026. Here is who is in scope, what changed in the standards and how to adapt your data and process.
OpenTelemetry in 2026: Building a Vendor-Neutral Observability Strategy
OpenTelemetry has become the default way to collect telemetry. Here is what changed in 2026 and a practical roadmap for a vendor-neutral observability stack.
Build a Faster, Leaner Logistics Network
Book a free consultation to discuss visibility, ETA, optimization or warehouse priorities with our logistics team. We reply to every enquiry within 24 hours.
Logistics FAQ
Can you integrate data from carriers and partners with very different systems?
Yes. Integrating heterogeneous partner data is at the core of most logistics projects. We work with EDI messages, carrier APIs, telematics feeds, spreadsheets and portal exports, and map them into a common shipment and event model. Data quality checks flag missing or inconsistent events so issues can be addressed with partners. Over time, we help you move partners toward more structured, standards-based feeds.
How accurate can ETA predictions be?
Accuracy depends on the mode, the quality of location and event data and the length of the remaining journey. Predictions generally become more precise as a shipment approaches its destination. We measure your current ETA accuracy as a baseline, then train models on historical performance and live signals and report improvements using agreed metrics such as the share of arrivals within a given time window.
Do optimization tools replace our planners and dispatchers?
No. Optimization engines generate high-quality plans quickly, but planners remain responsible for decisions and handle situations the model cannot know about. We design tools so planners can adjust constraints, lock decisions and understand why a plan was proposed. Adoption is much higher when planners help shape the tool, so we involve them throughout design and piloting.
What is the EU eFTI Regulation and how can you help?
The EU Regulation on electronic freight transport information (eFTI) establishes a framework for companies to share regulatory freight information with authorities digitally, through certified eFTI platforms, instead of on paper. Authorities are required to accept electronic information once the framework is fully in place. We help logistics companies structure their freight data, digitize existing documents and integrate with eFTI platforms and service providers as they become available.
How do you calculate logistics emissions?
We use recognized methodologies such as the GLEC Framework and ISO 14083, which define how to calculate greenhouse gas emissions for transport chains and hub operations. Calculations use actual data such as fuel consumption, distance and load where available, and recognized default values where it is not. Results can be reported per shipment, customer, lane or mode and integrated into customer reporting and decarbonization planning.
How quickly can a logistics data project deliver value?
A focused pilot, such as ETA prediction for one trade lane or route optimization for one depot, can typically be delivered in about three months, depending on data access. A broader visibility platform is usually built in phases. We provide weekly written updates and sprint demos, and we measure results against agreed baselines so the business case for scaling is clear.