For fleet operators, third-party logistics providers, distributors, and warehouse businesses that need real-time visibility and smarter operations from dispatch to final delivery.
Tools we wire together
LN
Live signal
Every card below is a working pattern we've shipped or scoped for a real logistics & supply chain client — not a wishlist.
Real-time GPS with automated route optimization. Save fuel, cut late deliveries, and give customers accurate ETAs.
Mobile apps for drivers — signatures, photos, geo-tagged confirmations. Works offline in low-connectivity zones.
Barcode scanning, live stock visibility across all locations. Eliminate manual stock counts and the errors that come with them.
Branded tracking pages and account portals — customers track shipments, raise tickets, and book pickups without calling ops.
Auto-generate invoices from delivery data, reconcile against POD, and chase disputed amounts — closing the order-to-cash cycle.
ML-driven volume forecasts by lane, customer, and SKU — turning capacity planning from spreadsheet guesswork into a model.
Lane-level capacity dashboards, hub-utilisation forecasts, and middle-mile load balancing — turning capacity decisions from gut-feel into a model.
On-time, fuel efficiency, safe-driving, and customer-rating scorecards per driver — feeding fair incentive payouts and retention conversations.
IoT temperature loggers, breach alerts, and audit-grade temperature charts per consignment — for pharma, food, and frozen logistics.
Tools typically used
ReactAWSPostgreSQLMaps APINode.jsLNLocoNavThese are the workflows that quietly drain margin, staff time, and patience. Every system we build starts from one of these.
Customer service spends half its day repeating the same answer: 'we'll check and call back'. Visibility lives on driver phones, not on a dashboard.
SLA breaches surface in next-month reports — by which time the customer has already escalated and the deduction is in your invoice.
Signed challans go missing. Disputes drag for weeks. Working capital sits stuck against deliveries you've already completed.
Dispatchers plan routes the same way they did in 2015. Fuel costs climb every quarter and nobody can tell you which lane is bleeding.
Monthly cycle counts surface 5–15% variance. Picking errors are routine. The WMS your last vendor sold isn't being used the way it should.
Invoices generated from one system, PoDs in another, customer disputes in email. Reconciliation eats 4 days a month from your finance lead.
Specific, working uses of LLMs and ML in real logistics & supply chainoperations — not generic “AI-powered” marketing.
Daily route plans optimised on real traffic, lane history, vehicle constraints, and driver hours — saving fuel and tightening ETAs without changing fleet.
Trip-level ETA prediction using historic lane data, real-time GPS, and traffic — so customer-portal ETAs don't have to be padded by 50% to be safe.
Drivers speak; the app logs PoD details. The camera captures and OCRs damage notes, packaging condition, and signatures — no typing in a moving cabin.
Lane- and SKU-level volume forecasts for capacity planning, hub staffing, and vehicle procurement — replacing seasonal guesswork with a model.
Real-time flags on idle vehicles, route deviations, fuel-card misuse, and dwell-time outliers — turning shrinkage and pilferage from monthly findings into instant alerts.
Customer raises a deduction; an LLM agent pulls the relevant PoD, GPS trail, and dispatch notes, and drafts a response — your team approves and sends.
A four-stage framework with AI capability called out at each step — so you can see exactly where machine learning earns its keep.
We ride along on dispatch, talk to drivers, and audit your current TMS / WMS stack. You leave with a written plan covering visibility, settlement, and route gaps.
AI-assisted lane and SLA analysis on your last 90 days.
We ship the highest-value workflow first — usually live GPS + PoD capture, or auto-settlement against PoDs. Live in one branch, with real drivers and ops using it.
LLM-bootstrapped data model and seed automations for dispatch + PoD.
Hub-by-hub rollout with driver training, parallel-run, and a customer-portal launch. We're at the hub during cutover, not at the office.
Auto-mapping of legacy CSV/Excel data into the new TMS/WMS schema.
Monthly review of OTIF, fuel cost per km, PoD turnaround, and invoice-dispute cycle. Quarterly tuning of route models and forecasts.
Anomaly alerts on route deviation, fuel anomalies, and dwell-time drift.
Every system we ship comes with the controls and audit surface your inspectors will ask for — designed in from day one, not bolted on later.
Native e-way bill generation and extension flows, FASTag integrations for toll reconciliation, and audit-grade evidence linking each trip to its compliance documents.
Vehicle, driver, fitness, permit, PUC, and insurance records tracked with expiry alerts. Compliance shifts from a fire-drill to a calendar.
Place-of-supply rules, reverse-charge applicability for GTA, and e-invoice flows handled cleanly — with reconciliation into Tally / Zoho Books built in.
Customer and driver data handled with explicit consent, purpose limitation, and data-principal request workflows — including for GPS trails.
Concrete scenarios, scoped from real conversations. Each one is a pattern we'd execute on day one.
Tell us where you are. We'll scope it, estimate it, and walk you through exactly how we'd approach it.
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