One Number Everyone Agrees On,Updated Daily
Sales, stock, collections and costs pulled from every system into one dashboard — with plain-language questions instead of waiting three days for a report.
- Works with spreadsheets
- Updated automatically
- Ask in plain language
- Live in 4–8 weeks
Every source in one place
ERP, POS, spreadsheets and bank data reconciled into one view.
Ask in plain language
'Which products lost margin last quarter?' — no SQL, no analyst.
Refreshed automatically
Yesterday's numbers ready before you get to the office.
Forecasts, not just history
Demand and cash-flow projections from your own patterns.
What is AI business intelligence?
AI business intelligence combines conventional reporting — pulling data from your systems into dashboards — with models that answer questions in plain language and project likely outcomes. Instead of requesting a report and waiting, a manager types a question and gets a chart with the figures behind it. The prerequisite is unglamorous: the underlying data has to be consolidated and consistent first. Most failed BI projects fail there, not at the dashboard.
Reporting that survives contact with real data
The dashboard is the easy part. Making six systems agree on what 'a sale' means is the project.
- Consolidation across your systems
- We pull from your ERP, POS, e-commerce platform, spreadsheets and bank statements into one model — including reconciling the definitions, so head office and branch stop reporting different sales figures for the same day.
- Plain-language questions
- Ask in Bangla or English and get a chart with the underlying rows, so anyone can check where the number came from.
- Dashboards per role
- The owner, the sales manager and the warehouse each see the handful of numbers that change their decisions, not one dashboard with forty tiles.
- Forecasting and anomaly alerts
- Demand and cash-flow projections from your own history, plus alerts when a figure moves outside its normal range.
- Automatic refresh
- Scheduled updates with a visible timestamp and a failure alert, so nobody presents a stale number without knowing.
What changes after launch
- 1×
- Meetings stop starting with an argument about whose figure is right.
- ↓
- Nobody spends Monday rebuilding last week's spreadsheet.
- 1st
- Alerts on unusual movement instead of finding out at month end.
- ✓
- Every figure traceable back to the transactions behind it.
One agreed set of numbers
Days of manual reporting removed
Problems seen sooner
Decisions with evidence
From scattered spreadsheets to one source of truth
We start with the five questions you actually need answered, not with the data you happen to have.
Swipe to see all 5 steps →
Common ways businesses use it
Sales and margin analysis
Which products, branches and customers actually make money after discount and cost.
Inventory and demand planning
What to reorder and when, based on real movement rather than instinct.
Collections and cash flow
Who owes what, ageing by customer, and a projection of what will actually land.
Branch and staff performance
Comparable figures across locations, on the same definitions.
- Wholesale & Distribution
- E-commerce & Retail
- Manufacturing
- Financial Services
- Logistics & Delivery
- Restaurants & Hospitality
- Healthcare & Clinics
- Education & Training
The numbers, and where they came from
Overview — last 7 days
Live৳48.2L
Revenue
+12%
vs last month
৳9.4L
Receivables
Dhk
Ctg
Syl
Khl
Raj
Bar
Ran
Alerts
Margin
InvestigatePackaging line below 8%
Stock
Action needed17 SKUs under reorder
Cash
On trackCollections ahead of forecast
Headline figures, the trend behind them, and the transactions underneath — because a number nobody can trace is a number nobody trusts. Sample data shown.
Questions, answered
01Our data is in spreadsheets. Is that a problem?
It is extremely common and workable. Spreadsheets can be brought into the pipeline directly. The real question is consistency — whether the same column means the same thing every month — and we assess that during the data audit.
02Do we need to replace our ERP first?
No. We read from what you have. Replacing a working system before you understand your reporting requirements is the wrong order, and often the wrong decision entirely.
03How accurate are the forecasts?
They depend on how much clean history exists and how stable your patterns are. Two years of consistent sales data produces something useful; six months across a period of disruption does not. We report accuracy on held-out historical data so you can judge it yourself.
04How much does BI cost in Bangladesh?
The main variable is the number of data sources and how messy they are, not the number of dashboards. We quote after the data audit, which we can run as a short paid engagement before you commit to the full build.
05How long does it take?
Four to eight weeks for a first set of dashboards from two or three sources. Consolidating many systems with conflicting definitions takes longer, and we will say so at the audit stage rather than partway through.
06Can staff ask questions in Bangla?
Yes. Plain-language querying works in Bangla and English, including mixed phrasing.
07Who can see which numbers?
Access is set by role, so a branch manager sees their branch and the owner sees everything. Salary and margin data can be restricted to named people.
Related services
- ERP & Business Management SoftwareThe main source most dashboards read from.
- AI Workflow AutomationAct on what the numbers reveal.
- AI Knowledge Base & RAGAnswers from documents rather than data.
- AI Document IntelligenceGet paper records into the data set.
- API Development & System IntegrationConnect the systems the data lives in.
- Custom AI AgentsAssistants that monitor the numbers for you.
Start with the five questions you cannot answer today
A short call about what you need to know weekly, and an honest view of whether your current data can support it.