dataeze unifies your Shopify, Meta and 3PL data and puts a team of AI analysts on it, so anyone can ask a question in plain English and get one number the whole team trusts.
Alum 200ml looks like a hero on revenue, but .
DOCap COD on Alum 200ml in tier-3 pincodes; push the 100ml there instead.
Contribution = net revenue minus COGS, fees, shipping and RTO cost, per SKU.
SELECT sku,
SUM(net_rev - cogs - fees - ship_cost - rto_cost) AS contribution
FROM sku_pnl
WHERE sku = 'ALUM-ROLL-200'
GROUP BY 1;
Lose 5 orders today and the dashboard calls it 0.1%. To those 5 customers, it was 100%.
Averages are where growth quietly dies. Your reports round the misses away; we build the foundation that catches every single one.
Every answer is one governed number, the plain-English why, the exact action to take, and the SQL that produced it. This is the analyst on every desk.
Four walls every scaling brand hits. Your data is scattered across Shopify, Amazon, Meta and your 3PL, apps you do not own, and every one reports its own number. We take the whole chain end to end: unify the data, govern every metric, and put an AI analyst on every desk. You will recognise all four.
Shopify, Amazon and Meta each report a different figure for the same metric, and you own none of them. Bigger teams get the same split across sales, finance and the dashboard. The meeting ends in a debate, not a decision.
Every question routes through the one analyst who knows where the data is buried. They take leave, and the report never comes. The call either waits, or gets made on gut feel.
The topline looks fine, and the detail is scattered across 6 vendor exports, so nobody slices deep enough. The leak, or the upside, is always one cut deeper.
The number lives in a vendor dashboard nobody opens between reviews. You are always a week behind the problem.
Investors diligence the numbers long before they diligence the deck. A brand that can trace every metric back to the query that produced it answers diligence in days, and defends its valuation with evidence instead of narrative.
Every AI pilot you have run put a brilliant driver on broken roads: 14 disconnected systems, 3 definitions of revenue, no map. It answered anyway, confidently. The model was never the problem. The road is.
dataeze builds the roads. The governed semantic layer under your stack is the reason the AI tells the truth.
Sources: AtScale natural-language query benchmark; enterprise text-to-SQL accuracy studies, 2025-26.
Not another tool on the shelf. The foundation underneath all of them, built inside your infrastructure, live in 2 to 4 weeks.
This is how the road gets laid. Anyone can demo a chatbot on clean slides; almost no one can make it trustworthy on your live data. Here is why ours holds up.
Every source, via API, DB or file, into one warehouse: de-duplicated, reconciled, standardized. No rip-and-replace of what you already run.
One governed definition of every metric. The single source of truth, and the hard part everyone skips. This is our specialty.
A conversational agent and function-wise dashboards on top, trusted from the boardroom to the last mile, every answer traceable.
Parse intent, entities and time frame.
Decide the metrics, dimensions and filters.
Map to the governed semantic layer.
Compose validated SQL, execute on live data.
Sanity-check totals, grain and nulls.
Answer, root cause, next action, traceable.
We build the entire system, the data layer, the semantic layer, the dashboards and the agent, inside your own server or cloud project. dataeze stores none of your data. Role-based access at the semantic layer, every query logged and traceable.
The foundation is the same everywhere; the semantic layer makes it yours. The questions the agent answers, and the kind of answer it gives back.
The same foundation also runs for BFSI, Healthcare & Pharma, Manufacturing and Tech / GCC teams. If that is you, let's talk.
A sample of what we run in production today, across very different businesses.
One foundation. Every desk gets the same truth, turned into their next move.
Every source, Shopify · Amazon · Blinkit · B2B, self-healed nightly and reconciled into one number then handed to each desk as an action:
We prep a live teardown of your stack before the call. Name, work email, and a time, that is all.
dataeze is 22 years inside the engine rooms of Indian business, from the sales floor to the boardroom, now productized.
We have strong opinions, formed running real data in production. Three of them, plus field notes in Insights below.
Text-to-SQL scores below 20% accuracy on ungoverned schemas. The fix is not a smarter model, it is the boring layer underneath. The governed semantic layer is what gets you to 90%+, and it is the part everyone skips.
dataeze point of viewEveryone demos the chatbot. The reason it survives a board meeting is one governed definition of revenue, margin and churn. We build that first, on every engagement, before a single question is ever asked.
dataeze point of viewTeams do not lack charts. They lack a number they trust enough to act on before the meeting ends. Everything changes when you design backwards from the decision, instead of forwards from the data.
dataeze point of viewdataeze is founder-led, with a senior network activated per engagement. The people who scope your problem are the people who build it. No pyramid of juniors learning on your budget.
Airtel's regional sales floors. Strategy desks at Dainik Bhaskar and HT Media. Trade and distributor data at SC Johnson. Then 6 years at Lenskart, Head of Analytics to AVP Global Pricing & Growth, on the road to its IPO, running Owndays analytics across Japan and Southeast Asia along the way, and AI-first analytics at Cars24 after that.
dataeze is that experience, productized.
Connect on LinkedInHow to make your data tell the truth, then put it to work on every desk. Written from real production, not theory.
Point a chatbot at 14 disconnected systems and it will confidently give you 3 different revenue numbers, none of them right. The problem is not the model, it is the foundation underneath it.
Your reports disagree because revenue, orders and CAC live in a dozen tools that never met. A governed semantic layer writes every definition down once, so an AI analyst and your whole team reason from the same truth.
When finance, growth and ops each pull their own version of last month's revenue, every meeting starts by arguing about whose number is right. One governed number ends that, backed by the exact SQL that produced it.
A dashboard answers the 20 questions someone anticipated 6 months ago and stays silent on the one you have right now. An AI analyst lets anyone ask in plain English and returns a traceable answer with the exact action.
Most brands do not lack data, they lack the decision. Four walls stand in the way, and naming them is the first step to tearing them down.
By the time a monthly report tells you a SKU went out of stock or CAC spiked, the damage is already booked. Live alerts close the loop the moment something moves, while you can still act on it.
Want these applied to your data? Book a 20-min working session →
dataeze (dataeze.ai) is an AI-first data and analytics firm for growing consumer brands. We rebuild your data foundation so AI can tell the truth about your business, then put a team of AI analysts on every desk, so anyone can ask a question in plain English and get a traceable answer with the exact action to take.
Founders and operators at scaling direct-to-consumer and SME consumer brands across D2C, FMCG and wellness, who are drowning in disconnected data across Shopify, Amazon, ads and spreadsheets.
A dashboard shows charts and waits. dataeze governs one trusted number, answers questions in plain English in seconds, and traces every answer back to the exact SQL query that ran. No black box, no analyst bottleneck.
Everything runs on your own infrastructure. dataeze builds the data layer, semantic layer, dashboards and the AI agent inside your own server or cloud, with role-based access and every query logged. dataeze stores none of your data.
Most brands are live in 2 to 4 weeks, not the 6 to 12 months a data-team build takes, because the foundation and the AI analysts are productized.
Operators, not researchers, with 20-plus years of enterprise data experience across companies like Lenskart, Cars24, Owndays, SC Johnson and Airtel, now productized for growing consumer brands.
dataeze is not another tool. It's an end-to-end solution that puts an AI-first analyst on every desk, budget-friendly, with ROI in multiples. Pick a 20-minute slot and we will show you the first 3 things we would fix to get you to one number your whole team trusts.
Already in production for Phitku, the Shark Tank India personal-care brand, plus REDMAT Pilates, Kokuyo Camlin and The Pant Project.
Just your name, work email, and a time. We prep a live teardown of your business before the call.
Prefer to reach out directly? Email hello@dataeze.ai · WhatsApp +91 99103 55559
