Stop digging through dashboards.Start getting answers.
Your channels joined, your questions answered by AI that knows Indian commerce.
Every team is doing their job. Nobody has the full picture.
Your performance marketer is scaling Meta. Your ops lead is replenishing Blinkit. Your CFO is hunting for contribution margin. None of them are reading the same numbers.
Your ads, storefront, fulfilment, B2B accounts and quick-commerce shelves have never been joined on one model.
You need more than a dashboard. You need to be told what to do.
Pause MFlash_Hindi_Prospect_v3. The audience is saturated. Scaling 3× tomorrow loses ₹2.4L this week.
Every pillar of your business. One model underneath.
P&L
Revenue, COGS, ad spend, shipping, returns. Joined to one true contribution margin per SKU, channel and campaign.
Google
EasyecomAttribution
Ads → customer activity → sales → returns, joined. True lift per channel and campaign.
Retention
Traffic cohorts next to purchase cohorts. Split by acquisition source, channel, campaign.
Quick-Commerce Availability
SKU × city × platform availability, with market data. Not just your own out-of-stock log.
Zepto
InstamartB2B Sales & POs
Buyer accounts modelled first-class. PO value, deadlines, fulfilment risk, prioritization queue.
Reliance
DMartMarketplace Analytics
Sales and ads side-by-side across horizontal and vertical marketplaces. One SKU graph.
Flipkart
Myntra
AjioCreator Analytics
Spend, content, and contribution margin per creator. The full loop from brief to repeat buyer.
Fulfilment & Returns
Returns by courier, city, payment, reason. The margin tax most dashboards can't see.
ClickpostPlanning
Daily and monthly sales, ROAS, COGS targets with variance built in as a measure.
Demand & Cashflow Forecasting
Demand forecast by channel. Cashflow forecast from those channels. Safety-stock recommendations.
The full operating picture.
The wedge.
AI is only as good as its semantic layer.
Ocular's is designed to work best in India. The dimensions Indian omnichannel commerce actually runs on are first-class in our model, modelled once and shared by every screen and Ocular AI.That's the moat, and the reason Ocular AI works.
What changes by day 30.
Onboarding isn't a slide. It's a thirty-day curve from kickoff to first margin-recovery action.
- Day 0· kickoff
We start.
Solution engineer assigned. Account scoped.
- Day 13 connectors
First connectors live.
Usually Shopify, Meta, Google.
- Day 75 dashboards
P&L and Attribution on your data.
Plus Ad & Campaign Performance, Ad Fatigue, Retention cohorts.
- Day 1411 connectors
Full stack connected.
Quick commerce, B2B, GA4, courier, planning targets.
- Day 301 action
First margin-recovery action.
Two fatiguing ads paused. One PO re-sequenced. One city prioritised.
We start.
Solution engineer assigned. Account scoped.
First connectors live.
Usually Shopify, Meta, Google.
P&L and Attribution on your data.
Plus Ad & Campaign Performance, Ad Fatigue, Retention cohorts.
Full stack connected.
Quick commerce, B2B, GA4, courier, planning targets.
First margin-recovery action.
Two fatiguing ads paused. One PO re-sequenced. One city prioritised.
The margin shift Ocular flagged on day six, you act on it on day seven. Not at quarter-end.
Plans scale with usage and the modules you turn on, not with seats.
Turn on the channels you run. Inventory & Planning and Ocular AI with your dashboards read across all of them. Build the plan, then book a demo that ends in a number.
They structure review calls around your reporting timelines, so the team is ready for every business review.
Bring the questions.
We brought the model.
Thirty minutes. You see Ocular. We see your stack. You leave knowing if it's a fit.
No follow-up email maze. No quote-builder. No phone queue. Thirty minutes. An honest fit decision at the end.
