The AI-Native TMS for Freight Forwarders.

An AI-native TMS is a transport management system where AI does the operational work, not just the record-keeping. A traditional TMS stores what people type into it; an AI-native TMS reads the inbound email, prices the RFQ, creates the shipment, and pushes the tracking update itself. Zavin is built this way from the ground up — the AI is the operating layer, not an add-on.

Zavin runs AI agents across the full forwarding lifecycle: an email agent that reads and answers inbound mail, a pricing agent that turns RFQs into margin-aware quotes in under 30 seconds, agents that create shipments from bookings, parse rate sheets into a company rate database, and push schedules and tracking to customers automatically — with human approval control at every step.

With one connected platform: the RFQ email is parsed, partner and carrier rates are collected and compared, a branded quote goes out in under 30 seconds, and the booking confirmation becomes a live shipment with documents and milestones — no re-typing. Zavin runs this end-to-end, cutting RFQ processing time by up to 85%.

No — most teams run Zavin alongside their existing TMS. CargoWise and Magaya are systems of record; Zavin is the execution layer that reads email, quotes, creates shipments, and sends updates. It connects to both, plus major carriers via EDI and API, so you can adopt it without a migration project. Teams go live in under 14 days.

A traditional TMS records work after humans do it in email; an AI-native TMS does the work at the point it arrives. The practical difference: with Zavin, around 50% of routine email volume is handled end-to-end by AI, quotes leave in under 30 seconds, and shipments are created with zero manual data entry — while a traditional TMS waits for someone to type.

Yes. Zavin is branch- and country-aware with field-level and object-level access control, so each office sees exactly what it should. Every AI action is recorded in a full audit trail, approval thresholds are configurable per workflow, and customer data is never used to train shared models. Enterprise security review and DPAs are supported.