AI for logistics in India

Logistics and courier operations in India run on a constant stream of text: e-way bills, delivery exceptions, customer status queries, dispatch notes. unoblox puts every major language model — GPT, Claude, DeepSeek, Qwen, Llama and more — behind one OpenAI-compatible endpoint billed in rupees, so a logistics team can add drafting, summarisation and multilingual support to its stack without opening a foreign-currency account.

The document and message load logistics teams handle

A mid-sized logistics operation generates exception notes when a delivery is delayed, customer queries about shipment status, dispatch summaries for warehouse handoffs, and driver or vendor communication — often in more than one language. Language models are a natural fit for drafting replies, summarising exception notes for a supervisor, and turning a warehouse log into a readable daily summary, with a human confirming anything customer-facing.

Text extraction versus scanned documents

If the source is already text — a typed manifest, an emailed exception note, a system-generated e-way bill — any general-purpose model can summarise or extract fields from it directly. If the source is a photo or scan, such as a handwritten delivery challan, that needs a vision-capable model; on unoblox, qwen/qwen3.8-27b is the open-weight model with vision input, so route image-based extraction there rather than a text-only model.

Picking a model by task and volume

Model	₹ / 1M input	₹ / 1M output	Typical use
qwen/qwen3.8-27b	0 (free)	0 (free)	Free pilot for a status-update bot
deepseek-ai/deepseek-v4-flash	9.11	18.21	High-volume status message drafting
meta-llama/llama-4-scout-17b-16e-instruct	10.12	30.36	Fast exception-note summarisation

Other models, including the rest of the OpenAI and Anthropic lines, are on unoblox too — see live rates on /models before choosing.

A quick integration example

curl https://api.unoblox.ai/v1/chat/completions \
  -H "Authorization: Bearer ub-gw-xxxxxxxxxxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/llama-4-scout-17b-16e-instruct",
    "messages": [{"role": "user", "content": "Summarise this delivery exception note for a supervisor."}]
  }'

The same key and base URL work for every model in the catalogue, so a pipeline can start on a cheap model and move specific steps to a stronger one without re-integrating.

Being direct about data and control

unoblox does not optimise routes, manage fleets or replace a transport-management system — it is a language API that your own systems call for drafting, summarising and translating text. And except for the free, unoblox-hosted qwen/qwen3.8-27b model, the other models here run on their original providers' infrastructure rather than inside India, so the India-specific benefit is rupee billing, a GST invoice and one endpoint — not data residency.

Frequently asked questions

Can this read a photo of a delivery challan or GST document? Only with a vision-capable model such as qwen/qwen3.8-27b, which accepts image input. Text-only models need the content already as text.

Does this replace our route-optimisation or TMS software? No. It's a language API for drafting and summarising text; routing and fleet decisions stay with your existing systems.

Can it draft delivery updates in regional languages? Yes, using a general multilingual model — review translations before sending to customers, especially for place names and timing details.

Is shipment or customer data hosted in India? Only for unoblox's self-hosted models, such as the free qwen/qwen3.8-27b. Other models run on their original providers' infrastructure outside India.

Is there a free tier to test before paying? Yes, qwen/qwen3.8-27b is free to call for prototyping.

How does GST invoicing work across multiple depots or entities? Usage across every model is paid from one rupee wallet, with a GST tax invoice issued at each top-up, with input tax credit claimable under normal conditions.

Get started in rupees → https://unoblox.ai/sign-in