Dashboards report the past. We predict what happens next.
BlackSwan Foresight gives mid-market Indian manufacturers predictive analytics and prebuilt scenario forecasts on their existing Tally or ERP data: demand, cash flow, supplier risk and customer risk. No SAP, no Oracle, no data-science team. Designed to be live in about two weeks.
- Collections DriftReceivables
- Big Buyer StretchConcentration
- Festive Demand MissDemand
- GST / ITC BlockageTax
- Limit CutBanking
- RM SpikeInput costs
Pick one, choose Bad, Worse or Black Swan, and see when a cash gap would open.
From last month's books to next quarter's decisions.
Three parts, one source of data. Start wherever the pain is sharpest.
Know what breaks first.
Eight preshocks Indian manufacturers actually face, from collections drift to a CC/OD limit cut, with the cash-gap date, runway and DSCR for each.
Run a scenario →Four predictive models.
Demand and reorder points, trapped working capital and cash gaps, the order book, and customer concentration and default risk.
See the models →Readouts, not dashboards.
Your data is checked, forecast and stress-tested, and you get specific recommended actions. A person always decides.
See the process →Business intelligence reports the past. Decision intelligence projects the future.
Power BI and Tally dashboards show you last month: sales booked, stock on hand. BlackSwan Foresight projects what happens next and recommends what to do about it, using models a dashboard tool doesn't include.
| Power BI / Tally | BlackSwan Foresight | |
|---|---|---|
| Tells you | What happened | What will happen, and what to do |
| Stress testing | Build it yourself in Excel | Eight prebuilt preshocks, one click each |
| Method | Visualises historic data | Predictive models and scenario arithmetic |
| Needs a data team | Yes, to build and maintain | No, models included |
| Time to value | Weeks of dashboard-building | Design target of about two weeks on existing Tally data |
Where dead stock hides in plain sight.
Here's the kind of readout a mid-size footwear manufacturer running on Tally, with no data team, gets from a single ledger export: a demand forecast across fast- and slow-moving lines.
73 slow-moving SKUs · ₹1.8 crore of overstock
In this example, the forecast flags roughly ₹1.8 crore of overstock across 73 slow-moving SKUs, while 11 fast-moving lines are quietly stocking out: the kind of pattern a monthly Tally report never surfaces.
Design target from export to forecast: about two weeks · New software installed: none
Find out what your Tally data already knows.
Start with the free AI-readiness assessment, or book a 30-minute discovery call to see a forecast built on your own numbers.