From last-mile fleets to enterprise 3PLs, T7 builds AI systems that cut fuel, speed up deliveries, and turn logistics paperwork into structured data.
Logistics margins live and die on the last 10% — the mis-routed vehicle, the missed pickup window, the LR that took three days to reconcile. T7 Solution builds AI that squeezes cost and time out of every leg: route optimisation, document AI, fleet telemetry and ETA forecasting integrated into your TMS or built ground-up.
We serve last-mile fleets, LTL/FTL operators, 3PLs and enterprise shippers. Our systems handle multi-modal shipments, cross-border customs docs and Indian LR/POD paperwork realities.
Every deployment is instrumented with cost-per-shipment, on-time rate and driver-behaviour KPIs — because in logistics, if you can't measure it weekly, you can't improve it.
Static routes leave 15–25% fuel and time on the table versus dynamic multi-stop optimisation.
LRs, PODs, invoices and customs docs still flow as scanned PDFs — slow to reconcile and error-prone.
Manager finds out about breakdowns, detours or aggressive driving after the fact.
Customers expect Amazon-grade ETAs; most fleets still guess.
AI models that plan multi-stop routes and consolidate loads dynamically.
Extract shipment, invoice, and customs data from PDFs and scans automatically.
Driver behaviour scoring, predictive maintenance, and real-time tracking.
Forecast shipment volume and delivery windows with production-grade ML.
Extract structured data from invoices, forms, IDs and reports with 95%+ accuracy.
Explore serviceProduction ML for forecasting, churn, risk and pricing — trained on your data.
Explore serviceAI-native automation that reads, decides and acts across your systems.
Explore serviceCustom vision models for quality control, retail analytics, medical imaging and more.
Explore serviceExplore how T7 Solution delivers logistics AI locally — with on-site discovery, compliance patterns and language coverage tuned to each market.
No. We integrate with your existing TMS via APIs and add AI where the ROI is highest — routing, document AI, ETA and telemetry.
We model vehicle capacity, driver hours, time windows, load type, gate timings and traffic — and expose overrides for dispatchers.
Yes, with 90–95% field accuracy using layout-aware OCR + LLM validation, plus a review UI for the rest.
Routing and document AI typically pay back in 3–6 months on medium-sized fleets.
Use cases, insights and comparisons chosen for logistics teams evaluating AI.
Straight-through processing for accounts payable — from PDF to ERP.
Draft first-pass underwriting notes with citations, in minutes.
Real-time fraud scoring across payments, claims and identity.
LLMs are not always the right tool. A decision framework — with real cost-per-inference numbers — for choosing between generative and classical ML in enterprise workloads.
How to design, build and deploy AI agents that plan, call tools and take real actions inside enterprise workflows — without breaking production.
OpenAI direct vs Azure OpenAI for enterprise
Self-hosted open-source LLM vs managed frontier API
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