BlackSwan Foresight
How It Works

From Tally books to decisions you can act on.

No new ERP and no data team. Here is what happens between sharing your data and getting your first readout.

  1. You share your Tally data

    We start from the ledgers you already keep: sales, purchase, stock, and receivables and payables registers. Today that means a Tally export; a direct Tally connection is being built so updates flow without manual exports. Around 24–36 months of history works best, and seasonal demand forecasts need at least 24 months.

  2. We check whether the data can be trusted

    Before any model runs, data-quality checks look for gaps, duplicates and entries that don't add up. You get a fix list for your accountant, and weak data is flagged rather than hidden. The Data Trust step also reconciles your books with GST and bank records.

  3. Four Foresight™ models build your baseline

    SupplyChain forecasts demand and reorder points. Finance finds trapped working capital, projects cash gaps and flags unusual ledger entries. Revenue forecasts the order book and Customer scores concentration and default risk. Each uses a method suited to its own data, documented in our AI Model Card.

  4. You get a readout, not a dashboard

    Each readout shows the forecast, the exceptions worth your attention (named SKUs, ledger entries, accounts) and a specific recommended action for each. Nothing is executed automatically: you or your finance lead decide.

  5. Preshocks test what could break

    Prebuilt Scenario Forecasts run named preshocks, such as collections drift, a big buyer paying late or a bank cutting your limit, against your baseline. Each run shows when a cash gap would open, your runway, DSCR and drawing-power headroom.

What we need from you

  • Tally exports of your sales, purchase, stock and receivables and payables registers.
  • A finance or accounts contact who can answer questions about the books.
  • For Prebuilt Scenario Forecasts: your bank sanction letter (limits, drawing-power margins, covenants), GSTR-2B data and a list of MSME-registered suppliers.

How long it takes

The design target is about two weeks from receiving your data to a first readout, because there is no new ERP to install. The exact timeline depends on how clean the data is and how much history you have, and we agree it during the discovery call.

What sits underneath

BlackSwan Foresight is built as an agentic system using the Model Context Protocol (MCP): a set of specialised tools, each doing one job, coordinated by an agent that runs them in the right order for your request. That keeps each step explainable and auditable, instead of one opaque model.

Straight answers

The questions promoters actually ask.

How can a mid-size Indian manufacturer do predictive analytics without SAP?+
BlackSwan Foresight runs predictive models directly on your existing Tally data — so there's no need for SAP, Oracle, or a separate data-science team. It forecasts demand, predicts cash-flow gaps, and flags supplier risk, and the design target is a go-live in about two weeks.
How is this different from Power BI or Tally dashboards?+
Power BI and Tally dashboards are business intelligence: they visualize what already happened. BlackSwan Foresight is decision intelligence — it predicts what will happen next (demand, cash flow, supplier disruption) and recommends an action, using AI models a dashboard tool does not include.
Is my financial and customer data safe?+
Yes. We don't train any public AI model on client data. Our founder holds an AI Security & Governance certification from Securiti, and data handling follows a documented governance approach informed by the NIST AI Risk Management Framework and ISO 42001. Your financial and customer data is kept segregated by design and used only to generate your forecasts.
How long does implementation take?+
The design target is about two weeks, because BlackSwan reads your existing Tally data rather than requiring a new ERP. A comparable enterprise system like SAP or Oracle typically takes six to twelve months and a dedicated data-science team.
What is the agentic / MCP architecture you use?+
BlackSwan Foresight is built on an agentic architecture using the Model Context Protocol (MCP). Specialized AI agents read your Tally data — supply-chain, finance, sales, and customer data — and coordinate to produce forecasts and recommended actions, rather than a static dashboard a person has to interpret.
What AI/ML techniques are actually running under each model?+
Each model uses a technique matched to what its data actually supports: Holt-Winters time-series forecasting and a statistical safety-stock model for SupplyChain Foresight (with a separate method for genuinely intermittent-demand items); isolation-forest anomaly detection on ledger transactions for Finance Foresight; and a trained credit-risk model shared between Revenue and Customer Foresight that scores probability of default from payment-history patterns. Full technical disclosure is in our published AI Model Card (PDF).
What are Prebuilt Scenario Forecasts?+
Prebuilt Scenario Forecasts run eight named preshocks (collections drift, a big buyer paying late, a festive demand miss, GST input credit getting blocked, the 45-day MSME payment rule, a bank limit cut, a raw-material price spike and a weaker rupee on imports) against your numbers at Bad, Worse or Black Swan severity. Each run shows when a cash gap would open, your runway, DSCR against covenant and liquidity headroom, with actions to take.

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.

Book a discovery call