Logistics · Generative AI & RAG
Every SOP and tariff rule, one question away.
Retrieval across standard operating procedures, tariff schedules, carrier contracts and customs requirements — with the source rule attached to every answer.
- Retrieval pipelines
- Fine-tuned domain models
- Multimodal (text · image · voice)
- Eval + guardrails
What we build
Generative AI & RAG for logistics, specifically.
- 01
Operator SOP assistant
Procedure retrieved by lane, mode and customer, so a new operator follows the process the account actually agreed to.
- 02
Tariff and documentation lookup
Requirements and restrictions retrieved with the governing rule cited, drafted for a licensed broker to confirm rather than acted on directly.
- 03
Contract terms retrieval
Carrier rate cards, surcharge terms and SLA clauses answerable in seconds — usually the first place clients find money they'd been giving away.
What we measure
- Accuracy on an operator-graded question set
- Citation correctness on tariff answers
- Onboarding time for new operations staff
Instrumented in week one and reported weekly. These are the numbers the engagement is judged on — not a forecast of what they'll be.
Constraints
What has to be true in logistics.
- 01
Extraction accuracy is measured per counterparty
One carrier's invoice layout is a solved problem; another's scanned fax is not. We report accuracy per source so automation is enabled where it's earned.
- 02
Customs and tariff answers get citations or nothing
Classification suggestions carry the source rule and go to a licensed broker for confirmation. An unsourced HS code is a fine waiting to be issued.
- 03
Integrations fail, so the design assumes it
Carrier APIs and EDI feeds go down mid-shipment. Retries, dead-letter queues and a visible degraded state beat a silent gap in tracking.
How it runs
The Generative AI & RAG engagement, step by step.
- 1
Data inventory
What docs / databases / APIs / feeds matter? What's PII vs public? What changes daily vs quarterly? We map it before writing code.
- 2
Retrieval architecture
Hybrid (BM25 + vector) retrieval, chunking strategy, reranking, citations. Tuned for your domain not a generic benchmark.
- 3
Eval suite
Real-world question set with golden answers. Faithfulness, context precision, latency. So you know when changes ship a regression.
- 4
Guardrails
Prompt-injection defense, PII scrubbing, refusal patterns, output schemas. Especially critical for customer-facing deployments.
- 5
Production + iterate
Cost-effective inference (caching, fallback models), monitoring, weekly eval reports. Fine-tune when the data justifies it.
Integrations
Systems we wire into for logistics.
- Carrier and 3PL APIs
- EDI (X12 / EDIFACT)
- SAP & Oracle SCM
- Shiprocket & Delhivery
- Customs broker portals
- Snowflake
- Twilio & WhatsApp Business
FAQ
RAG for supply chain documents: your questions.
Can it classify HS codes?
It can suggest, with the governing rule cited, for a licensed broker to confirm. Autonomous classification is a customs penalty with extra steps, and we won't build it that way.
Our SOPs are out of date. Should we fix them first?
No — index them first. Indexing surfaces the contradictions and the dead procedures faster than a documentation project will, and gives you a prioritised list to fix.
Should I use RAG or fine-tuning?
RAG for facts that change. Fine-tuning for style, format, or domain reasoning. Most production systems use both — and we'll tell you which mix is right after a 1-week discovery.
Can I use my own LLM (open-weights)?
Yes. We work with Llama, Mistral, Qwen, and similar — useful for data residency, cost predictability, and air-gapped environments.
Contact
Talk to us about generative ai & rag for logistics.
Two or three sentences about the workflow you'd start with. We reply within one business day.
Or skip the form — book a Calendly slot directlyadmin@neuroxai.com · +91 70149 99768
Remote-first team across India · US · EU · HQ in Udaipur, India
More for Logistics
Other work we do in this vertical.
- AI agents for logistics operationsAgents that detect a shipment exception, gather the facts from carrier and document sources, notify the right party, and escalate with the file already assembled.Read
- 30-day AI sprint for logisticsPick the exception that costs the most operator hours. We ship working software against it in 30 days with an eval score, or you don't pay.Read
Same service, other industries
Generative AI & RAG elsewhere.
- RAG for banking and financial servicesRetrieval over circulars, product terms and internal procedure — returning the clause, the revision date, and a link to the page it came from.Read
- RAG for healthcare and clinical documentsRetrieval over clinical guidelines, payer policy and internal SOPs — with the citation, the version, and an explicit refusal when the library doesn't cover the question.Read
- AI product search and catalogue RAGSemantic search and grounded product Q&A over your catalogue, reviews and size guides — with stock and price read live rather than remembered.Read