/ 01 — Mission

Tell people why a locality is a smart choice, not just where to look.

Ooru — Kannada for one's own place, one's town — is the AI locality-intelligence engine for Bangalore house hunters. It combines real air quality, verified school proximity, and metro access into a reasoned advisory a person can trust and revisit. ooru.maahaa.dev

/ 02 — The problem

What we actually solve

Rental discovery in Bangalore is solved by maps and listings. bengaluru.rent shows real crowdsourced rents on a Google Map with zero friction. 99acres and Magicbricks show volume. None of them answer the decision question a family asks: is this a good place to live, and why?

That question needs quantitative livability — clean air, good schools nearby, a workable commute — turned into a clear, reasoned recommendation. That is the gap. That is the only thing Ooru needs to be excellent at.

/ 03 — The one rule

Honesty comes before features

The advisory must only state findings the pipeline actually computed. Right now it does not — and that is the single most important thing to fix.

Integrity blocker · verified in code

The report claims "ICSE schools nearby" and "metro under 3km", but the school and metro nodes return {} — that data never reaches the LLM. The claims are hardcoded boilerplate. Until this is fixed, Ooru is less trustworthy than a competitor with no analysis at all, because it asserts findings it never made.

/ 04 — Where we win

Reasoning and memory, not the map

Not on the map. bengaluru.rent has a multi-year crowdsourced rent-data lead and a frictionless, no-login model. Racing them on pins and matching is a losing fight.

We win on the two things they structurally lack: verified multi-factor reasoning (AQI numbers, school distance, metro access, fused into a judgement) and authenticated personal memory (saved searches, history, side-by-side comparison). Their strength is data volume. Ours is intelligence and trust.

Map tools show you where people rent. Ooru tells you why a locality is — or isn't — a smart choice.

/ 05 — Success criteria

What good looks like

/ 06 — Read next