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হ্যালো
হ্যালো

i. the support engineer · 2015 / 2018

Three years in support, watching analytics fail the people it was built for.

CSAT on the line. Customers angry. Ten analysts servicing fifty teams, all asking the same question phrased five different ways. Nobody could self-serve.

  • Learned SQL just to do my own job.
  • 500+ conversations resolved slower than they should have.
  • Collected the complaints. They became a spec sheet.

ii. cto & co-founder · 2021 / 2024

Learnt from 300+ operators. Built a Custom Success Product. Then killed it.

Full-stack: backend, frontend, infra, integrations, devrel. One engineer, one market. $125K pre-seed from Upekkha on a SAFE.

  • Five tools. Five definitions of "healthy customer."
  • Zero shared language.
  • Found the real problem lurking underneath CS.

iii. the pivot · customer success → core data analysis

It was never a CS problem. It was a foundation problem.

Every interview pointed the same way. The gap between "we have data" and "we understand what it means" was wider than any tool could bridge. Better UIs on broken foundations still give confident wrong answers.

  • Text2SQL gave confident wrong answers. Worse than none.
  • The infrastructure assumes you already know what to measure.
  • Killed the product. Kept the problem. Rebuilt the foundation.

400+ tools. same 5% served.

Data analysis should be for everyone.

Not just for companies who can afford a data team. Not just for people who already know what to measure. For the other 95%.

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Beliefs

deck

01
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Feelings > Features

01
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A feature only works if it makes someone feel something. Nobody remembers specs. Everyone remembers how a tool made them feel.

02
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Experiments > Experience

02
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Testing fast beats following what used to work. Experience becomes a cage if you stop questioning it.

03
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Product is Marketing

03
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Separating them is the most expensive mistake I've made. The product IS the pitch.

04
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Open Source is the Future

04
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Hard mode. But the only way to build trust in a world drowning in hype.