Northeast India

Recommendation & Personalisation across Assam

Recommendations that lift the metric you care about, measured by experiment, not by offline accuracy. Covering every district and PIN code in Assam.

Districts
23
PIN codes
571
Cities mapped
14

Recommendation & Personalisation in Assam

Offline accuracy and revenue are different things. We measure recommendations by experiment against the business metric, because that is the only number that pays anyone.

Assam runs on tea, petroleum and natural gas, agriculture and handloom and silk, plantation and energy operations spread across difficult terrain, which makes remote monitoring and field-data capture the recurring need. Where recommendation & personalisation earns its budget here usually follows directly from that mix.

We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep. You own the code, the models where they are open-weight, and the documentation to run it without us.

নমস্কাৰ , Nomoskar. We work in Assamese and English across Assam.

Assam coverage

State / UT
Assam
Region
Northeast India
Districts covered
23
PIN codes covered
571
Cities mapped
14
Working languages
Assamese, English

What is included

  • Event tracking design, since most projects start with inadequate data
  • Baseline popularity model to beat
  • Hybrid collaborative and content-based ranking
  • Cold-start handling for new users and new items
  • A/B testing framework with proper statistics
  • Business-metric reporting, not just offline accuracy

Questions

Do you cover all of Assam?

Yes, all 23 districts and 571 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which Assam sectors do you work with most?

Across Assam the economy leans towards tea, petroleum and natural gas, agriculture, handloom and silk. Plantation and energy operations spread across difficult terrain, which makes remote monitoring and field-data capture the recurring need.

How much data do we need?

Less than people assume to start. A content-based approach works from day one; collaborative filtering improves as interaction volume grows.

How do you handle new products?

Content-based features carry new items until interaction data accumulates, with deliberate exploration so new items get a fair chance to be seen.

How do we know it is working?

Controlled A/B tests measured on revenue or engagement, with proper statistical treatment rather than eyeballing a dashboard.

Recommendation & Personalisation in Assam

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

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