AI solutions for logistics that move the plan, not just the dashboard
We build AI solutions for logistics and transportation operators: routing and scheduling optimizers benchmarked against your current planner, fleet telemetry that predicts a breakdown before the driver reports it, warehouse cameras that count, verify and protect, and order and shipping-document automation that posts to the ERP without re-keying. Measured in on-time deliveries, planning hours and exceptions caught early.
Logistics is an optimization problem with the data in six systems
A transport operator holds vehicles in a telematics platform, orders in an ERP, stock in a warehouse system, routes in a planner's spreadsheet, customs documents in email and customer promises in a CRM. Every delay is a mismatch between two of them. Route optimisation AI and fleet management AI only help when the plan they produce reaches the dispatcher and the driver, and when it is measured against what the planner would have done anyway.
Where we deliver: in UAE, for operators preparing for the 2026 e-invoicing rollout and handling driver and customer data under UAE PDPL; in Saudi Arabia, for fleets serving Vision 2030 logistics hubs under ZATCA e-invoicing, the SDAIA PDPL and NCA ECC-2:2024; in India, for operators working with GST e-invoicing and e-way bills under the DPDP Act 2023; and in United States, for carriers under FMCSA rules with customer data practices mapped to state privacy laws. Our offices are on the locations page.
Six logistics workflows we engineer, from route plan to proof of delivery
Each card names the systems it connects and the number it moves. Pilots start with one depot, one lane or one document type.
Route and schedule optimization
Vehicle routing with time windows, driver hours and vehicle constraints, solved with classical and quantum-inspired methods and benchmarked against your planner's actual routes before anyone is asked to trust it. Read our quantum-inspired optimisation approach.
Warehouse computer vision
Existing dock and aisle cameras count pallets, verify loading against the manifest, detect forklift danger-zone entry and flag missing PPE, processed on site through VisionGuard AI. Warehouse video analytics with evidence attached to every alert.
Fleet and asset telemetry
Telematics, engine diagnostics and fuel data in a time-series platform, with per-vehicle baselines that flag a failing component before it strands a load. Alerts become workshop bookings, not a red icon on a map.
Learn more →04Demand and capacity forecasts
Volume by lane, depot and day forecast from order history, customer calendars and seasonality, so fleet and warehouse capacity are planned a week ahead with error reported in pallets or trips.
Learn more →Shipment status automation
Purchase orders, booking requests and shipping documents read from email, PDF and portals, validated against rates and stock, and posted to the ERP through AI Order Automation, with status updates sent to customers and exceptions queued for a person.
Operational command dashboards
On-time performance, utilization, exceptions and cost per trip calculated once in a governed data layer, so dispatch, finance and customer service read the same number.
Optimization, edge analytics and data engineering, with the solver honestly benchmarked
Our logistics work combines optimization engineering, edge video analytics, streaming data platforms and workflow applications. The optimization team runs classical solvers and quantum-inspired methods such as QUBO formulations and annealing-style heuristics side by side, and reports which one won on your instance sizes. Quantum hardware will not beat your solver this year; quantum-inspired methods running on ordinary servers sometimes will, and we show you the benchmark either way.
Quantum-inspired optimization is where we start with logistics clients; full quantum deployments do not exist yet, in our portfolio or at scale anywhere, and we say so. What a logistics operator gets today is a better-tested classical or quantum-inspired plan, integrated with dispatch, and a clear statement of where the frontier actually is.
A worked example: from late deliveries to a benchmarked route plan in dispatch
Suppose a distributor's urban delivery fleet misses time windows and planners spend three hours each evening building routes by hand. Here is how that becomes an optimizer the dispatcher trusts, with order intake automated upstream.
- 01
Quantify the late deliveries
Missed windows, planning hours, kilometers per drop and failed deliveries are counted for one depot over a quarter. That depot becomes the pilot.
- 02
Map orders, fleet and constraints
ERP orders, telematics, vehicle capacities, driver hours and customer time windows are mapped, along with how routes currently reach drivers.
- 03
Define the benchmark
The planner's actual routes for the quarter are the baseline. Targets: kilometers, windows met and planning time, with no plan accepted that violates driver hours.
- 04
Prototype the solver
Classical and quantum-inspired formulations are run on the same historical days. Results are compared against the planner's routes and against each other, and the winner is reported with its running time.
- 05
Validate with dispatch and security
Dispatchers review a month of proposed routes in parallel. IT reviews telematics data access, driver data handling under UAE PDPL or DPDP Act 2023, and the ERP integration.
- 06
Integrate order intake and dispatch
AI Order Automation posts clean orders to the ERP each afternoon, the optimizer produces routes from them, and dispatch pushes them to drivers with the ability to override and record why.
- 07
Monitor and extend
Windows met, kilometers per drop, override rate and planning time are reviewed weekly. The next depot joins once the first holds through a peak month.
How value is measured on the road and in the warehouse
Success is counted in delivery reliability, planning time, exceptions detected before the customer calls, vehicle and warehouse utilization, and the route-cost assumptions the optimizer was given versus what the fleet actually spent. The baseline comes from your telematics, ERP and planning records before the first solver run.
We test through the conditions that break plans: a festival peak, a road closure, a vehicle off the road at 6 a.m. If the optimizer cannot beat the planner on your instances, the report says so and we keep the planner.
Governance for driver data, cameras and cross-border documents
Logistics AI touches driver location and behavior, warehouse video of staff and customs or tax documents, so three sets of rules apply. Driver data is processed with notice and purpose limits, video runs on site with no biometric retention unless there is a lawful basis, and document automation is designed to work alongside each market's e-invoicing and e-way bill regime rather than replace your tax filing.
By market: UAE PDPL, the 2026 e-invoicing rollout and UAE Information Assurance standard for government-linked operators in UAE; the SDAIA PDPL, NCA ECC-2:2024 and ZATCA Fatoora in Saudi Arabia; the DPDP Act 2023, GST e-invoicing and e-way bills in India; and FMCSA hours-of-service rules plus state privacy laws in United States. Your legal and security teams review every proposal before go-live.
Why logistics operators work with Constient
Because we benchmark before we recommend, and we integrate what we recommend. The optimizer, the telemetry platform, the warehouse vision and the order automation come from one group, so the route plan reaches the driver and the order reaches the ERP without a third vendor in between.
We have built infrastructure monitoring platforms for distributed GCC sites, vision pipelines for safety and the AI Order Automation product. Savings in kilometers or hours are measured on your depot against your planner, and reported whether or not they flatter the solver.
Frequently asked questions
How does a logistics AI engagement with Constient start?
With a discovery session on one depot, lane or document type where the pain is measurable: missed windows, evening planning hours or re-keyed orders. We confirm data access across telematics, ERP and warehouse systems, take the baseline from your own records and scope a fixed-price pilot. Routing pilots always include a benchmark against the plans your team actually ran.
Is quantum-inspired optimization ready for a real fleet?
Sometimes, and we will tell you when it is not. Quantum-inspired methods run on ordinary servers today and can beat classical heuristics on some routing and scheduling instances; on others the classical solver wins. We run both on your historical days and report the result. Quantum hardware is not part of a production plan this year, and we do not cite client quantum deployments because we have none yet.
Can you integrate with our telematics, TMS and ERP?
Yes. We ingest from telematics providers through their APIs, connect to transport and warehouse management systems where interfaces exist, and post orders and routes to Dynamics 365 Business Central, SAP or Oracle. Where a system exposes no API we use scheduled exports. Interface availability and licensing are confirmed in discovery so the pilot is not blocked midway.
Where does driver, customer and video data stay?
In your region and your tenant. Warehouse video is processed on site and only counts, alerts and evidence clips leave the building. Driver and customer records are handled under UAE PDPL, the SDAIA PDPL or India's DPDP Act 2023 as applicable, with notice to drivers and retention schedules agreed with your legal team. Data flows are documented before the pilot starts.
How is logistics AI work priced?
Discovery and the single-depot pilot are fixed price. Rollout across depots is a fixed-price build with a support agreement or a dedicated engineering team billed monthly. AI Order Automation and VisionGuard AI are licensed products with implementation priced separately once volumes and sites are known. Solver benchmarking is included in the pilot, not charged as research.
Build a logistics technology roadmap starting with one depot
Bring the late deliveries, the breakdown rate or the order backlog. We will map the systems, benchmark the plan against your planner and propose a bounded pilot.