Our team builds AI features, data pipelines and BI dashboards for US companies, inside your own cloud accounts and US regions rather than ours. Fixed scope, fixed quote, documented handover. We are in India, so US mornings are the live overlap window and the rest of the work runs async with written updates. This is the US view of our AI, data and visualization service.
Your cloud, your US regions.
Most US engagements start with one of these and grow into another, because a dashboard is only as good as the data behind it and an AI feature is only as good as both.
GenAI and large language models wired into the products and workflows your US teams already run: retrieval over your own documents so answers cite your content, summarisation and extraction where people currently read and retype, and natural-language querying over data you already hold. The build sits in your accounts, so the documents and the vector store stay in the regions you chose rather than moving somewhere you did not pick. Where a simpler rule or a well-built report would serve you better, we will say so before you pay for a model.
Ingestion and transformation on a schedule you can rely on, warehouse or lakehouse design so the data lands somewhere queryable, and the unglamorous data-quality work that decides whether anyone in the business believes the output. US estates are usually a mix: a CRM, a billing system, a product database, a warehouse someone started two years ago, and spreadsheets holding the seams together. Two systems disagreeing about the same customer is a data problem, and no chart will paper over it.
Reporting in Power BI, Tableau or Amazon QuickSight, chosen on where your data lives and what your people already use rather than on what we prefer to build. Self-serve analytics so teams answer their own questions instead of queuing for a report, and executive reporting that says what changed and why instead of showing everything at once. A dashboard nobody opens after week two was a scoping problem, not a charting one, which is why the scoping call comes first.
Delivery is remote, so the two questions worth answering early are where your data sits and how the working day actually overlaps. Here are both, without the marketing gloss.
The honest version: you get live conversations in your morning and steady written progress the rest of the day, in your own US accounts.
Three steps, no open-ended retainer required, and no dependency on us at the end unless you decide you want one.
A call in your morning to understand the data you have, the decisions you want to make with it, and what is in the way. We come back with a fixed scope and a written quote in USD. If a smaller piece of work would answer your question, that is what gets quoted.
Book a scoping callThe work runs to the agreed scope, built inside your own US accounts and regions. You see progress as it lands instead of waiting for a reveal, with live reviews in your morning and written updates in between. Scope changes come with a number before they happen.
You get the build, the documentation and a handover session with the people who will run it day to day. Everything stays in your environment, so nothing sits in a black box only we can open. Ongoing support afterwards is a separate conversation, not a condition.
The offer is the same everywhere. What changes per market is the region your data sits in and how the working day lines up.
What we build across AI, data engineering and business intelligence, how engagements are scoped, and what you get at handover.
London and Ireland regions for UK and EU data, with your morning overlapping our afternoon so reviews happen live inside the UK workday.
Delivery on the AWS UAE and Bahrain regions where in-country residency matters, on a working day that runs almost in parallel with yours.
Sydney and Melbourne regions for Australian data, with standups and reviews that fit inside the Australian workday rather than at the edges of it.
Mostly about regions, working hours and how the contract is handled. If your question is not here, ask it on the call.
Bring the data you already have and the decision you are trying to make with it. We will tell you what is realistic, what it would take, and what it would cost, in writing and in USD, before you commit to anything.
