[ Logistics software either lowers cost per delivery or it does not matter ]
Logistics software either lowers cost per delivery or it does not matter. Every feature — route sequencing, dispatch rules, proof of delivery, exception handling — should trace back to a line in that equation. Techtaru Digital is a logistics software development company that builds with that framing, delivering custom logistics software development across TMS platforms, fleet management, last-mile delivery and the driver apps that hold it together in the field.
Logistics software either lowers cost per delivery or it does not matter. Every feature — route sequencing, dispatch rules, proof of delivery, exception handling — should trace back to a line in that equation. Techtaru Digital is a logistics software development company that builds with that framing, delivering custom logistics software development across TMS platforms, fleet management, last-mile delivery and the driver apps that hold it together in the field.
Share your delivery volumes and failure modessystems modelled on your depots, shift patterns and exception types rather than a generic template.
freight, line-haul and distribution systems for shippers and carriers.
driver, dispatcher, customer and warehouse apps.
carriers, telematics vendors, ERP, WMS, e-way bill, payment and notification providers.
incremental migration off spreadsheet-driven or ageing dispatch systems.
SLA-backed support with capacity planning for festive and sale peaks.
Order intake, load planning and consolidation, carrier allocation, freight rating, tendering, invoicing and claims. Our transportation management software development work suits shippers, 3PLs and freight forwarders alike.
Vehicle master, utilisation and idling, fuel and mileage, preventive maintenance schedules, tyre and spares, document expiry and driver compliance.
Multi-stop sequencing with time windows, vehicle capacity, service durations, driver shift rules and traffic conditions, with mid-route re-optimisation when a stop fails.
Slot booking, dynamic allocation, live ETAs, customer notifications, reattempt and NDR workflows, and hub-level performance visibility.
Task lists, turn-by-turn navigation, offline capture, cash collection, break and hours logging, and battery-aware location tracking.
Signature, photo, OTP and geo-stamped delivery evidence, with dispute-ready audit history.
Manual and automatic assignment, live dispatch board, exception queues, escalation rules and SLA countdowns.
Device ingestion, trip reconstruction, geofencing, idling and harsh-driving alerts, and driver scorecards.
Automated generation, part-B updates, validity tracking, extension handling and reconciliation against actual movement.
Cost per drop, on-time rate, first-attempt success, vehicle utilisation, carrier scorecards and lane profitability.
depots, shift patterns, exception types, and who decides when a delivery has failed.
event model for vehicles and consignments, solver selection, integration inventory.
driver app tested on real routes, not in an office.
one depot or one city proven and tuned before scale-out.
baseline cost per drop captured before go-live so improvement is provable.
Backend: Node.js, Go, Java, Python. Mobile: Kotlin, Swift, Flutter with offline-first local storage. Data: PostgreSQL with PostGIS, TimescaleDB or InfluxDB for telematics, Kafka for event streaming, Redis for live dispatch state. Routing: OR-Tools, Valhalla, OSRM, Google Routes API, HERE. Maps: Mapbox, Google Maps Platform. Integrations: Shiprocket, Delhivery, FedEx, DHL, e-way bill APIs, SAP and Oracle ERP, WMS platforms. Infrastructure: edge buffering for depot connectivity, autoscaling for peak dispatch windows.
Routing is a genuinely hard computational problem, and vendors who claim otherwise are selling a sorted list. Real-world routing is a vehicle routing problem with time windows, capacity limits, shift rules, vehicle restrictions and service durations — NP-hard, meaning optimal solutions are not computable at fleet scale. Practical systems use heuristics and metaheuristics to reach very good solutions fast. What matters is how long you allow for a solve, whether you re-optimise mid-route, and whether drivers can override without breaking the plan. We state those trade-offs rather than promising an optimum.
Telematics data volume surprises people. A thousand vehicles pinging every ten seconds produces roughly 8.6 million points a day. Storing that in your transactional database degrades the whole platform within months. The right pattern is a time-series store, aggregation at ingest, retention tiers, and geofence evaluation in the pipeline rather than the API layer. The same pipeline carries our telematics and connected vehicle work.
Driver apps must work without a network. Basements, rural corridors and steel warehouses all kill connectivity. Field-captured scans, signatures, photos and cash need a local queue with conflict-tolerant sync and clear UI state. Battery discipline matters equally — aggressive background GPS drains a shift.
Fixed scope for driver apps and integrations; dedicated squads for TMS and platform programmes; managed support for live fleets with defined response times.
Indicative cost: a driver app with tracking and ePOD typically starts around $20,000–$45,000. TMS and multi-module platforms run higher; phasing by depot or region keeps early cost contained. Timelines: driver app with ePOD and tracking, 8–12 weeks; last-mile delivery platform, 14–20 weeks; full TMS, 5–9 months phased.
Pick a logistics software development company that asks about your exception rate before your feature list. Share your delivery volumes and failure modes and we will return an architecture and a phased plan.
Usually yes. We ingest from common telematics providers and raw device protocols, normalise into one vehicle event stream, and keep the platform device-agnostic.
Let’s talk about your logistics project. No obligation, just a conversation.
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