I didn't plan to start a data studio. I started by building dashboards. For years I was the person companies brought in to make sense of their numbers — Power BI reports, data models, and the pipelines their decisions quietly depend on — across consulting and enterprise teams, and then independently as a Top Rated Plus builder on Upwork.
Project after project, one pattern got impossible to ignore: the dashboard was almost never the real problem. The chart everyone complained about was just the last visible symptom. The real problem sat upstream — the broken pipeline feeding it, three spreadsheets that should have been one system, a sharp analyst rebuilding the same report by hand every Monday, decisions made on numbers that were already two weeks old.
The shift that changed how I work
So I stopped handing over prettier dashboards and started fixing the system underneath them — modelling the data properly, automating the pipeline, and wiring the whole thing to run on its own. That's when the work actually stuck. Reports stopped breaking. The manual Mondays disappeared. People got their time back.
Then AI changed what one builder could ship. Using tools like Claude, I went from building reports to building complete products — full apps, not just dashboards. I'm honest about what I am: not a career front-end engineer, but a data and systems person who now ships finished software, fast, because AI closes the gap. The proof is live — Sello, an AI assistant that sells over WhatsApp, and Revora, a platform that ties ad spend to real revenue — both designed and shipped end to end.
That's what I'm actually building. Not dashboards. Not scripts. Time back, clarity, and systems that keep running long after the project ends.
Why I built Datavoris
Datavoris exists because most businesses deserve far better data infrastructure than they have — and they shouldn't need a ten-person data team to get it. What they need is someone who understands the technical side and the business side well enough to build something that fits how they actually work, and to ship it without a year-long project plan.
The name says the intent. Datavoris — data, devoured. Good systems should consume your data problems, not create new ones: automate the grunt work, surface the signal, and let people spend their time on what only people can do.
What I believe about data work
- The best dashboard is one you don't have to think about — it just tells you what you need to know.
- Automation should be invisible. If a system needs babysitting, it wasn't built right.
- Most "data problems" are actually process problems in disguise.
- Non-technical teams deserve tools they can actually use — not tools that require a technical team to interpret.
- AI is only useful when it's connected to real data and a real workflow. Otherwise it's just impressive-sounding noise.
What I've built
Where I'm taking this
Datavoris is growing from project work into a product studio — reusable engines, diagnostic platforms, and AI-powered tooling that a small team can run with almost no setup. The goal is simple: make the kind of data infrastructure that used to need a big team available to a small one.
If you're here because something's broken — a report that eats your week, a dashboard that answers the wrong questions, a process held together by copy-paste — that's exactly the kind of problem I like.
Tell me what's broken. I'll tell you how I'd fix it.
Founder, Datavoris · Agra, India