12 · 6 · 0
Twelve filters. Six tabs. No “why”.
Your team clicks through Region, State and Station, flips from Summary to MIS, and the chart still can’t say what caused the drop.
AI analytics for FMCG, CPG and retail
Analsiy connects to the data you already use, rebuilds your Tableau and Power BI dashboards in days, and puts AI on top from day one. Your systems stay exactly as they are.
Sales overview · October
All regions
Sale qty · month
392K
▲ 5.1%
Outlets billed
62,410
▲ 3.4%
Secondary vs plan
−4.2%
▼ East −12%
Secondary sales vs plan, by region
Ask AI
Why did secondary sales drop in East this month?
✓ Plan vs actual · ✓ 214 distributors · ✓ Stock and billing by SKU
Down 12% against plan. Three distributors explain 70% of the gap. All ran out of top-20 SKUs from the 9th.
What to doRefill those SKUs at the three distributors this week.
Sound familiar?
12 · 6 · 0
Your team clicks through Region, State and Station, flips from Summary to MIS, and the chart still can’t say what caused the drop.
2–3 days
“Why did East fall?” goes to the analytics queue and waits behind the MIS refresh and the new SKU report.
Meanwhile
Stock-outs spread, outlets stop billing, and the month closes before anyone can act on the answer.
How it works
Read-only connectors to the sources you already run, such as SAP, SQL Server, Snowflake, your distributor management system and Excel. Nothing in your stack changes.
We rebuild your Tableau and Power BI dashboards end to end, and check every number against the original before your team switches over.
Connect → Map → Rebuild → Validate → Live
Ask in plain English, from any chart or the Ask AI box. Get the answer, the reason behind it, and the next step for your team.
Answer · Reason · Next step
Ask AI
Click any number and ask why. Ask AI works through plan vs actual, distributors, SKUs and outlets the way your best analyst would, then tells you what to do about it.
Why did secondary sales drop in East this month?
Down 12% against plan.
Three distributors explain 70% of the gap. All ran out of top-20 SKUs from the 9th.
What to doRefill top-20 SKUs at these three distributors this week, and move beats to the 140 outlets that stopped billing.
Example answer on demo data.
Why switch
| Typical Tableau or Power BI setup | Analsiy | |
|---|---|---|
| “Why did sales drop?” | Raise a ticket, wait 2–3 working days | Ask, and get the answer in seconds |
| Finding the cause | Click through filters and tabs yourself | AI drills down to distributor, SKU and outlet |
| What to do next | Left to whoever reads the chart | A recommended action with every answer |
| Getting started | Months of rebuilding reports | Your dashboards migrated in days |
| Your systems | Stay as they are | Stay as they are, connected read-only |
Built for FMCG
Primary and secondary sales, distributors, outlets and SKUs come ready to use, not as a blank canvas your team has to build.
Primary and secondary sales against plan, by region, distributor and outlet.
Coverage, reach and how each distributor is performing.
Stock days at every distributor, and the sales you lose to stock-outs.
Which outlets are growing, slipping, or have stopped billing.
SKU velocity, mix and how new launches are landing.
Scheme and campaign impact on secondary sales.
Security
Analsiy reads from your sources and never writes back. Your current reports keep running while your team tries Analsiy side by side.
Connectors only read. Nothing in your sources is changed or deleted.
Keep your warehouse, ERP and current BI while you evaluate.
Free demo
No slides and no sample company. We show you answers from your own numbers.