What I build for businesses here
Bellandur and Sarjapur are mid-size product companies past their first version, almost always with in-house engineers. The work is a specific capability — AI features, a mobile app, a performance rescue.
Bellandur and the Sarjapur stretch are dense with mid-size product companies and funded startups — teams past the first version, usually looking for a specific capability rather than a full build.

I live and work in Bengaluru, so Bellandur is somewhere I can genuinely meet you rather than only work with you remotely. Across 70+ shipped projects, the ones that went best almost always started with an hour in a room deciding what not to build.
Teams here almost always have in-house engineers, so I am typically brought in for AI work, a mobile app, or a performance rescue. Bounded scope works far better than shared codebase ownership.
Multi-tenant SaaS platforms with subscriptions, auth, and admin panels — production-ready from day one.
Custom AI agents, OpenAI integrations, and workflow automation built directly into your product.
High-performance iOS & Android apps built with React Native — standalone or alongside your SaaS.
Next.js listing platform for pre-launch and under-construction Bangalore developments — unit-level inventory with per-configuration pricing and availability, and budget filtering that reasons across configurations rather than projects.
Next.js site for a curated luxury property advisory — a single search across property, location, city and builder, and a schema model that describes a consultative service rather than a listings catalogue.
WordPress build for a luxury real-estate services company across four cities — Elementor Pro templates over a JetEngine content model, JetSearch property search, and a handover the client's own team could operate.
Bellandur and Sarjapur are mid-size product companies past their first version, almost always with in-house engineers. The work is a specific capability — AI features, a mobile app, a performance rescue.
Adding AI to a product with real users is a different problem from a prototype: guardrails, logging, a fallback when the model is wrong, and a cost model that survives scale. I scope those as the work rather than as polish.
An AI capability added to an existing product runs ₹5–12 lakh depending on how many systems it touches. A performance rescue starts at ₹2 lakh and begins with measurement, not assumptions.
There is no team behind me and nothing is subcontracted. The person you scope the project with is the person writing the code, which removes an entire category of translation loss. The trade is capacity — I take a small number of projects at a time, and I will tell you if I cannot start when you need to.
The repository lives under your account and the cloud infrastructure is provisioned in yours. You should never be in a position where changing developer means losing your product. Handover documentation is part of the work rather than something negotiated at the end.
A deposit to start, then payments tied to milestones you can see working in a staging environment. Never the full amount upfront in either direction. If a project stops early, you keep everything built to that point.
Every project gets a written scope split into launch and later, with an explicit not-included list. That second list prevents most disputes, because disagreement almost always comes from an assumption nobody wrote down.
That is most of what I do now. Adding retrieval or agents to something with real users is a different problem from a prototype, and it is the more interesting one.
Usually, starting with measurement rather than assumptions. The bottleneck is rarely where the team expects, which is exactly why an outside look helps.
Let's talk.
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