AI Analytics
Anomaly detection, forecasting and plain-language answers over your own marketplace data.
What actually goes wrong
Dashboards tell you what happened. They rarely tell you that something is wrong, and never tell you first.
Why this matters. The useful question is not 'what were sales' but 'what changed, and does it matter'.
What SMEMinds does
- Anomaly detection across sales, fees, returns and ad spend
- Demand forecasting per SKU with seasonality
- Natural-language querying over your own reports
- Automated weekly brief ranked by rupee impact
- Root-cause suggestion for each flagged anomaly
- Grounding rules so every figure traces to a source report
Who this is for
Brands with enough data volume that manual review misses things.
Deliverables
- Anomaly rules
- Forecast model
- Weekly brief
- Query interface
What changes.
Stated as changes in how the business runs, because those are the ones we control.
Earlier warning
Anomalies surfaced in days, not at month end.
Better forecasts
Purchase decisions with a defensible basis.
Faster answers
Ask in plain language, get a sourced number.
Auditable output
Every figure traceable to its report.
Every recommendation shows its arithmetic.
The model is inspectable: inputs, weights and the arithmetic that produced the recommendation, not a score with no derivation.
See the toolsOr learn to run it yourself.
The models behind this service are taught in the SMEMinds AI Playbook — in Hinglish and English, with the calculators included.
Open the SMEMinds AI PlaybookQuestions we get about this service
Every figure is traced to the source report it came from. If a number cannot be sourced, the system says so rather than estimating.
Others in AI
Let's look at your account.
Tell us what the constraint is and we will tell you whether we are the right people to fix it.