Industries
AI for Logistics & Transportation
AIYatch builds AI for logistics, freight and delivery companies: ETA and delay prediction, route and load optimisation, shipping-document automation, and customer status assistants on chat and voice. Systems connect to your TMS, WMS and carrier APIs so dispatchers, customer service and finance teams work from the same real-time picture and spend less time on manual updates.
Typical challenges
- Customers ask “where is my shipment?” far more often than teams can answer.
- Bills of lading, customs forms and invoices are processed manually and cause delays.
- Delays are discovered late, so re-planning is reactive and expensive.
- Route and load planning leaves capacity unused.
Typical use cases
ETA and delay prediction
Models over historical shipments, traffic, weather and carrier performance that predict arrival windows and alert on likely delays.
Route and load optimisation
Optimisation and ML models that plan routes, consolidate loads and assign vehicles against constraints such as time windows and capacity.
Shipping-document extraction
Document AI that reads bills of lading, packing lists, customs and carrier invoices, validates them and files data into your TMS or ERP.
Shipment-status assistants
Chat, WhatsApp and voice agents that answer tracking questions, reschedule deliveries and log claims, escalating exceptions to staff.
Freight audit and invoice reconciliation
AI agents that match carrier invoices to contracts and shipments and flag discrepancies for finance to review.
Questions from this sector
Yes. The assistant calls your TMS, WMS or carrier tracking APIs in real time so answers reflect the current status rather than a cached copy. Where APIs are missing we work from database access or scheduled exports, and always with least-privilege credentials.
Accuracy depends on the richness of your historical data and external feeds. Typical projects aim to narrow arrival windows and catch a large share of delays earlier than the current process. We measure against your existing ETAs during discovery and report the improvement transparently.
Yes. LLM-based assistants handle dozens of languages by default, and voice agents can be configured with region-appropriate speech models. We test the languages that matter for your lanes and customers before launch, tune terminology such as service names and status codes, and make sure hand-off to a human agent carries the conversation in the original language.
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