East India

AI Infrastructure & MLOps across West Bengal

GPU infrastructure, model serving and MLOps pipelines, sized for your workload, not for a benchmark. Covering every district and PIN code in West Bengal.

Districts
23
PIN codes
1,147
Cities mapped
29

AI Infrastructure & MLOps in West Bengal

Cost per inference is the operating metric. We instrument it from day one so capacity decisions are made on evidence.

West Bengal runs on engineering and steel, jute and textiles, leather, tea and financial services, an older industrial base with substantial legacy-system modernisation work ahead of it. Where ai infrastructure & mlops earns its budget here usually follows directly from that mix.

We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong. Six weeks to something running in production, not six quarters to a strategy document.

নমস্কার , Nomoskar. We work in Bengali and English across West Bengal.

West Bengal coverage

State / UT
West Bengal
Region
East India
Districts covered
23
PIN codes covered
1,147
Cities mapped
29
Working languages
Bengali, English

What is included

  • Workload sizing based on measured throughput, not guesses
  • Model registry and versioned deployments
  • Autoscaling and cost-per-inference monitoring
  • Canary and rollback deployment paths
  • On-premise or air-gapped options where required
  • Runbooks and on-call documentation

Questions

Do you cover all of West Bengal?

Yes, all 23 districts and 1,147 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which West Bengal sectors do you work with most?

Across West Bengal the economy leans towards engineering and steel, jute and textiles, leather, tea, financial services. An older industrial base with substantial legacy-system modernisation work ahead of it.

Cloud or on-premise?

We model both against your real volume. On-premise typically wins at sustained high throughput or where data residency is non-negotiable; cloud wins on variable and early-stage workloads.

Can you deploy air-gapped?

Yes, with open-weight models and a fully offline inference stack, the usual pattern for defence, and for some healthcare and government work.

Do you support our existing Kubernetes setup?

Yes, and we would rather extend it than introduce a parallel platform your team has to learn.

AI Infrastructure & MLOps in West Bengal

Covering all 23 districts. Tell us what you are trying to change.

Or email bd@dtrasglobal.com · call +91 74118 77878