5 newspapers, 210 sub-editions, 12 states, on the street before sunrise. The numbers behind them arrive days late, from different rooms. Our AI agents close that gap: pulled, tallied, answered by 7am. Every day.
1,000,000+ orders reconciled to source1,000,000+ items modelled to margin4 businesses live in productionEvery answer on your own infrastructure
4 short chapters, about 3 minutes. The gap → decisions, faster → why it works → what it does for Dainik Bhaskar.
The gap
The decisions are daily. The data is not.
Print grows on yield and cost now. Both are speed games, and the speed is lost to assembly: pulling, cleaning, formatting, before anyone can ask the question.
Where decisions wait today
•Edition P&L closes at month-end. Decisions wait.
•Ad yield shows up after the quarter. Win-backs start late.
•Print and digital live in different rooms, on different numbers.
•Every review starts with days of spreadsheet assembly.
•Every new question joins an analyst queue.
What changes with agents on your data
✓Edition P&L open any morning, comparable across all
✓Slipping accounts surface weekly, with a win-back list
✓Returns tracked depot by depot, daily
✓One view: print and digital side by side
✓The 7am brief writes itself: what moved, why, who owns it
✓Any question, plain language, answered in seconds
Same people, same source systems. The assembly is what the agents take over.
How we help
6 decisions print leadership makes. Faster, with evidence.
Shaped for a newspaper group. All 6 run on one governed foundation, built once, inside your own cloud. Every slow version of these decisions is margin left on the table.
Ad sales · Yield
No account slips away quietly
• Every client and agency watched weekly, against last year • Win-back call goes while the budget is still on the table
Quarter-end → weeklydecision cadence
Editions · P&L
No edition loses money unseen
• 1 comparable P&L for every edition, any morning • Newsprint moves, pagination and rates move the same month
Month-end → any morningp&l visibility
Circulation · Returns
Every unsold copy is a priced decision
• Depot-wise returns, priced in newsprint, daily • Bundles fixed while the leak is small
Season-end → dailyreturns control
Print + Digital
One audience, sold as one story
• App and site numbers next to print, market by market • Digital stops selling at a discount
2 rooms → 1 viewpackaged selling
Events · Season
Own the season before the first booking
• Your booking history and season benchmarks, ready first • Rates set from evidence, not memory
Gut → benchmarksseason planning
Leadership · 7am
The 7am number nobody argues with
• Agents tally every source overnight and write the brief • Everyone starts on the same number. Zero assembly.
Days of assembly → 7amdaily MIS
Not a concept
6 systems, all live, all on the client's own cloud.
Not pilots. Each refreshes overnight and feeds real decisions next morning. A newspaper is the same shape: many sources, one truth, daily.
D2C · Personal careLive
Multi-channel commerce warehouse
Shopify, Amazon, quick-commerce and B2B pulled into one warehouse, with revenue reconciled to source every night.
1,000,000+orders, tied to the rupee
D2C · ApparelLive
Logistics and margin at item grain
Every shipment modelled down to the line item, so gross margin is visible by courier, lane and SKU.
1,000,000+items modelled
FMCG · StationeryLive
Self-serve executive dashboard
An 8-page board dashboard running on their own semantic model. No analyst sits in the loop.
8 pagesno analyst needed
Services · Multi-siteLive
Three booking systems, one truth
Three unconnected systems unified, with row-level access so each trainer sees only their own classes.
3 sourcesunified, row-level secure
ProductLive
The AI analyst itself
Multi-tenant agent: ask by chat or voice, export to PDF, schedule to email, get alerted when something moves.
13 languageschat, voice and mobile
FoundationsLive
The unglamorous part underneath
Nightly pipelines, stored procedures, reconciliation guards and health monitoring. This is what makes the rest survive.
60 min → 3 minnightly refresh, rebuilt
Capabilities
Not just answers. The whole workflow.
Everything the agent does around the question, all on your own live data.
Reports that come to you
Schedule any question to re-run on live data and land in your inbox and on Slack.
Just ask out loud
Tap the mic and speak your question. No typing, and it works on your phone.
Answers in your language
Ask in English, Hindi, Japanese and 10 more. The reply comes back the same way.
Bring your own files
Drop in an Excel, CSV or PDF, or paste a screenshot, and ask questions grounded in it.
Board-ready in one click
Turn any answer into a clean, branded PDF, ready for the meeting.
Role-based access
You decide exactly which data, and how much, each user or group sees. Right down to the row.
Every dashboard, live
Your existing Power BI reports, embedded in one place and always current.
Business context Coming soon
Connect Slack, email, WhatsApp and meeting notes so the analyst knows your world.
See the depth in action
Ask it anything. Get the depth, not just the number.
One agent, every function. The questions below are illustrative, shaped the way a newspaper group actually asks them. Each one gets the number, the why and the exact action, in seconds.
Growth · Revenue
2.1s
QWhy did we miss the revenue plan this month?
Revenue
₹42.6Cr
▼ 9% vs plan
Volume
▼ 12%
▼ below plan
Realization
▲ 3%
▲ price held
WhyNot price. 3 of 12 regions drove 80% of the miss on volume, while realization actually improved.
DoRegional heads: rebuild the demand plan for those 3 regions this week. Recoverable this quarter: ₹3.8Cr.
Always on, 24/7 with you
We spot it, before you miss it.
dataeze works alongside you, around the clock. It watches every metric and flags the moment something moves, an opportunity to grab or a loss to stop, so you act while it still counts and keep the business growing.
Opportunity
Jewellery bookings are up 2.4x this week across 3 editions. Push the category pitch while it lasts.
Live
Risk
Bookings from one agency are down 3 weeks straight. Win-back call before the quarter absorbs it.
Live
Anomaly
Returns in one depot are up 2x vs trend. Bundle allocation, not demand, is the cause.
Live
Newsprint risk
Newsprint at this price flips 7 editions margin-negative this month. Rebalance pagination today.
Live
Always on, working with you to grow the business, not just report on it.
The real reason AI disappoints
You cannot run a Tesla on a broken road.
Give a brilliant AI messy, ungoverned data and it guesses, then hands you a wrong answer. One wrong answer and no one trusts it again. The AI is not the problem. The road underneath it is.
≠ AI on messy data≠ Messy data✓ The road dataeze builds✓ dataeze road
Everyone is racing to run the Tesla. We build the road first, then let it fly.
Why this is hard to copy
Anyone can add AI. This is what they cannot copy.
Any capable team can wire up an AI. The moat is what builds up underneath it, and gets harder to copy every month you run.
It runs on your own infrastructure
Every pipeline, the semantic layer and the AI sit inside your environment. Your data never leaves. Most tools cannot offer this at all.
It compounds, and it locks in
The semantic layer gets richer every month. Once every team runs on one trusted definition, it becomes the source of truth, not a tool you can swap out.
We arrive with the models built
Metric models already proven across FMCG, D2C and logistics. Your build is faster because we are not starting from a blank page.
Traceable, and operator-built
Every number traces to the exact query that produced it, modelled by a 20-year operator who knows which metrics move a P&L.
The AI is the easy part. What compounds underneath it is the moat.
Under the hood
All your data, in one place you can trust.
The reason every answer can be trusted: it all runs on one clean, agreed version of your data, built once, up front, before a single question is asked.
ERP, sales & finance
Supply chain & WMS
CRM, marketing & web
Files, sheets & more
Bring it together
Every system pulled into one place, cleaned and matched up.
One source of truth
One source of truth
One agreed definition of every number, that everyone works from.
Ask anything
Ask in plain English; live dashboards for the board on top.
What this looks like for you
One region first. Then the nation.
Prove it in 1 region in weeks, live alongside the current MIS. Then scale what worked.
Track A · The POC
1 region, 4 to 6 weeks
Pick the region. We wire it end to end and run it daily, in parallel, so the comparison is honest.
✓Ad revenue by client, agency, category, with the rates you actually get
✓Circulation and returns by depot, daily
✓Region P&L, any morning, not month-end
✓7am brief: what moved, why, who owns it
Track B · National scale
Every edition, one governed model
210 sub-editions, 12 states, 3 languages, print, digital and radio, on one number everyone trusts.
✓Edition-wise P&L on one comparable basis
✓National vs local ad yield, every market
✓Digital next to print, one view
✓Ask in plain language, answers in seconds, traceable
4 to 6 weeks
to live on your own data
Value by week 3
first workstream shipped
About 1/3rd
of an in-house team's cost
Us vs the field
Everyone does a slice. We do the whole job.
AI copilots, AI-BI platforms and dashboards each cover a piece. Only dataeze does it end to end, on your own governed data.
dataeze
AI copilotsJulius, Vanna
AI-BI platformsThoughtSpot, Hex
BI dashboardsPower BI, Tableau
Runs on your own infrastructure
✓
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Fixes and governs the data first
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Answers in plain English, in seconds
✓
✓
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Every answer traceable to a query
✓
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✓
Watches metrics 24/7, flags risks
✓
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Live in weeks, we run it with you
✓
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Swipe the table →
Same features, or close, as the specialists. Only one does the whole job, on your own data.
Why you can trust this
20 years turning messy data into decisions.
This is not a lab experiment. It was built by an operator, not a researcher, on two decades of running data inside some of India's largest Telecom, Media, FMCG and consumer businesses, and it is already live in production today.
The foundation runs deep: he started in 2004, when sales reports were still totalled on calculators, long before the data ever touched a dashboard. That ground-up instinct for numbers, proven across telecom, media, FMCG and consumer, is what dataeze is built on.
Proof, on real businesses
Live in production. Already paying off.
Reconciled to the rupee
Numbers the board finally trusts
A D2C brand: every revenue number tied out to source across 1,000,000+ orders, with a costly double-count caught in the first month.
Days to seconds
Board questions, answered live
Questions that took an analyst days to pull are now answered in plain English, in seconds, by anyone who asks.
60+ min to under 3
Fresh data every morning
A nightly refresh rebuilt from over an hour to under three minutes, so every decision runs on today's numbers.
1,000,000+ shipments
Margin you could not see before
A logistics business, modelled end to end, with profit visible by courier, lane and SKU for the first time.
Shark Tank India
D2C · Personal Care
D2C · Apparel
Fitness · Studios
Kokuyo Camlin · Stationery FMCG
Live today across D2C, FMCG, retail and logistics. The same engine, ready for Dainik Bhaskar.
The invitation
Let us show you this on Dainik Bhaskar's own data.
Pick the region we start with, and one question you cannot answer today. Give us one export to work from. In a short working session we will show you the number, the reason behind it and the action, live, on your own data.
A daily newspaper decides daily. Every morning the numbers arrive late, or disagree, the day runs on gut. The sooner the road is built, the sooner that stops.
