Logistics AI is enterprise software in disguise: heavy on integrations, heavier on regulatory exposure, heaviest on cost-pressure. Margins are thin and software has to pay for itself fast. NKKTech ships logistics AI that survives the realities of multi-modal shipping, customs regulations across 10+ countries, and warehouse-floor hardware constraints. Used by freight forwarders, 3PLs, and B2B e-commerce ops across the US, Singapore, Japan, and Vietnam.
Six capability patterns we ship most often for logistics + supply-chain clients.
Bills of lading, commercial invoices, packing lists, customs declarations. Multilingual + multi-format (PDF, JPG, ZUGFeRD/Factur-X). 95%+ field-level accuracy on standard forms, lower on handwritten.
Multi-stop routing with time-window constraints, multi-modal (road + rail + sea + air) planning, dynamic re-routing on disruptions. Plugs into TMS (MercuryGate, Cargowise, Manhattan Associates).
SKU-level demand prediction by destination and seasonality, with confidence intervals. Reduces stockouts + over-orders. Integrates with WMS + ERP for execution.
HS-code classification, restricted-party screening, customs-document generation, multi-jurisdiction compliance checks. Always with human-in-the-loop for final filing.
Damage detection on inbound + outbound, pallet-count verification, dimension measurement from camera, hazmat-symbol detection. Edge-deployed on warehouse cameras.
Track-and-trace bots, exception-management agents (delayed shipments, customs holds), carrier-onboarding automation. Multi-channel (web, WhatsApp, EDI gateway).
1–2 weeks. Map your TMS, WMS, ERP, customs broker integrations. Identify integration constraints before designing AI.
6–10 weeks. Build narrowly (one document type, one route lane, one warehouse). Measure against current process.
8–14 weeks. Extend to adjacent flows; deepen TMS / WMS integration; build operator dashboards.
Monthly retainer. Customs regulations + carrier APIs change; AI must keep up.
Document automation, rate-quote generation, shipment-tracking bots, customs filing automation, carrier-selection optimization.
Inbound damage detection, putaway optimization, pick-path AI, outbound quality verification, labor-forecasting models.
HS-code classification, multi-country customs compliance, return-merchandise authorization automation, currency + tax automation.
Route optimization with traffic + weather, delivery-window-honor prediction, photo proof-of-delivery validation, recipient-not-home AI.
Temperature-deviation alerting, regulatory-document generation, traceability with serial-number tracking, GDP-compliant audit trails.
Container-damage detection from photos, port-arrival prediction, vessel-routing optimization, multilingual support for global crews.
Yes — Cargowise, MercuryGate, Manhattan, SAP TM, Oracle TM are all in our integration history. We also build custom integrations for proprietary TMS via REST or EDI gateway. Estimate 2–4 weeks for the integration layer in any project.
We design for multi-jurisdiction from day one. The AI doesn't make final customs filings autonomously — it generates classifications + draft documents that a licensed customs broker (or your in-house team) reviews and submits. We've integrated with broker workflows for US (CBP ACE), EU (CBAM + standard customs), Singapore, Vietnam, and Japan.
Document automation: payback typically 4–8 months at moderate document volume (5K+ docs/month). Route optimization: 2–6 months depending on route complexity. Demand forecasting: 6–12 months (need a full seasonal cycle to validate). Warehouse CV: payback longer (12–18 months) because of edge hardware investment.
Shipment data often contains PII (recipient names, addresses) and commercially-sensitive information (contracts, pricing). We use BAA-covered LLM providers for any PII, self-hosted Llama for commercially-sensitive content, structured access controls per-shipment, and audit logging on every data access. Same security model we use for healthcare and fintech.
USD 60K–150K for a pilot on one flow. Multi-flow scaled deployments: USD 200K–800K over 6–12 months. Recurring costs vary widely with volume; typical mid-3PL spend is $500–$5K/month for LLM + cloud infra.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Tony's team understood our legacy PHP system faster than our internal team. Zero downtime migration, exactly as promised. The bilingual PM made communication seamless.
We went from 15 hours/week of manual prospecting to fully automated lead gen in 8 weeks. ROI in 60 days as Tony promised.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
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30-minute free discovery call with a senior NKKTech engineer (not a sales rep). We'll review your requirements, scope an engagement, and tell you honestly whether we're the right fit.
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