Margin clarity for brands that can't afford to find out late
Consumer brands today operate across more channels than any prior generation — and the commercial complexity has grown faster than the tools. Most brands still reconcile margin in Excel, monthly, after the window to act has closed.
MIRA exists to change that. We believe every brand — not just the ones with a 30-person analytics team — should be able to see their real margin, in real time, across every platform they sell on.
Why we built this
The founding team spent years working with consumer brands expanding from India into the Middle East and Southeast Asia. The same conversation came up every quarter: the brand thought they were profitable on a new channel, then the platform reconciliation arrived and the real number was 12 points lower than expected. Commission structure had changed. The FX rate used in the model was last quarter's. A promotional top-up had been applied that nobody had accounted for.
The problem wasn't a lack of data — it was that the data lived in six places, in three currencies, with different update cadences. No single model held the real picture. MIRA is the model we wished existed.
How we build
These are the principles behind every product decision.
Your data is yours, always
Tenant isolation is enforced at four independent layers. One brand's COGS will never reach another brand's dashboard. This is a technical guarantee, not a policy.
No vendor lock-in by design
We use open data formats and industry-standard connectors — export your data anytime, point your BI tools directly at it, and move on if you ever need to.
Built for the world, not just India
Every monetary value in MIRA carries a currency code. The margin engine refuses to subtract INR COGS from USD revenue without an explicit FX conversion. Multi-currency is a type-system concern, not an afterthought.
The number is the number
The margin engine is deterministic and fully auditable. Given the same inputs, it produces the same output every time. When the number changes, it's because your data changed — not because our model drifted.