AI Development for
Logistics / Supply chain.
Logistics runs on routing, forecasting, and documents. All three are now LLM and ML-native problems. Vedwix builds ai development for Logistics / Supply chain companies — with the compliance posture, KPI awareness, and operational shape your category demands.
Brief us on AI workWhat we know about Logistics / Supply chain.
- SOC 2
- GDPR
- Customs / trade data
- On-time delivery
- Cost per shipment
- Forecast accuracy
- Brittle integrations across carriers
- Black-box forecasting
- Compliance variance across regions
Three use cases we ship.
Demand-forecasting agents
We build AI features that ship to real users — not demos. For logistics, that means designing for SOC 2, measuring against On-time delivery, and avoiding the brittle integrations across carriers that plague the category.
Route optimization at scale
We build AI features that ship to real users — not demos. For logistics, that means designing for SOC 2, measuring against On-time delivery, and avoiding the brittle integrations across carriers that plague the category.
Document automation for customs
We build AI features that ship to real users — not demos. For logistics, that means designing for SOC 2, measuring against On-time delivery, and avoiding the brittle integrations across carriers that plague the category.
AI Development,
logistics-aware.
We don't pretend every project is the same. Logistics / Supply chain has its own compliance, KPIs, and unwritten rules. We bring those in from day one.
Start a projectWhat you get.
- RAG system with hybrid search
- Eval harness + observability
- Agent orchestration
- Fine-tuning + serving
- Internal AI tooling
We build AI features that ship to real users — not demos. RAG systems with hybrid retrieval, agents with structured outputs, fine-tuned small models, and eval harnesses that measure quality before and after every change.
Examples of Logistics / Supply chain companies in this space: Flexport, Convoy alumni, Project44.