rithvik mittapalli

rithvik mittapalli

Building Bhuvam AI

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Building Bhuvam. A new approach to Market and Customer Research - Get insights in minutes and at fraction of a cost.

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Ensemble by Bhuvam AI - Your Research & Marketing Co-Pilot

Ensemble by BhuvamAI simulates customer journeys step by step. Synthetic shoppers move through your journey simulation, and you see exactly where each one drops off. Then chat with that shopper: ask why they left, what would change their mind, or how they’d react to a new price, creative, or packaging. Use it to decide what to ship next. The beta is built from public shopper reviews, not customer data, and supplements real research. Try it in your browser, no signup.

What if you could use a no-code tool to build agents and export it to your own code/website/product?

Every team building agents rebuilds the same plumbing: a tool layer, a RAG pipeline, connectors to their data, and some orchestration glue to chain prompts together. It's weeks of undifferentiated work before you ship anything a user sees.

We are building to be that layer, managed:

  • Tools give your agent capabilities without writing the harness

  • RAG attach a knowledge base, retrieval handled

  • Connectors plug into the systems your agent needs to read and act on

  • Prompt orchestration chain, branch, and route across steps

  • Metering every run is measured, so billing and cost visibility are built in, per agent

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2mo ago

Founders who rebuilt their app from scratch — was it worth it?

About eighteen months into our product, we hit a wall that wasn't a feature problem. Every new thing we shipped took roughly three times longer than the last comparable one. Bug fixes kept reopening. Two engineers had built quiet, undocumented workarounds around the same broken assumption in our data model, and neither knew the other had done it.

The obvious answer was a rewrite. We didn't do it not immediately. We spent a month arguing about it instead, which in hindsight was the most useful month we spent that year, because it forced us to name the actual problem: it wasn't the codebase. It was one early decision about how we modeled user accounts that everything else had been built to work around.

We ended up doing a partial rebuild. Roughly 40% of the code, the part that touched that assumption. Took four months instead of the fourteen a full rewrite would have taken. Shipping slowed but never stopped.

I still don't know if that was the right call. A full rewrite might have cleared out debt we're still paying for. Or it might have killed us the graveyard of startups that spent a year rebuilding while a competitor shipped is not small.

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