Outlets, B2B orders and the online store ran on separate systems, so stock, pricing and customer data never agreed. Margin was visible only after a nine-day month-end close, and GSTR-1 filing was a manual, error-prone monthly scramble.
Before building anything, we mapped the operation. These are the findings that shaped what we built.
The same product carried different prices and stock positions across channels — no single source of truth.
Month-end close took ~9 days, most of it manual reconciliation between billing, inventory and Tally.
GSTR-1 was assembled by hand each month, with filing errors and no HSN-wise confidence.
The data foundation, and the AI agents that turn it into decisions and action.
POS, B2B and outlet orders and a shared-catalogue e-commerce storefront transact against one product, pricing and inventory backbone — the single source of truth the agents run on.
Instead of a month-end scramble, an MIS agent assembles daily margin and store-KPI reporting and pushes it to leadership over WhatsApp within hours of close — while an anomaly agent flags pricing drift and unusual patterns across channels.
An agent assembles GSTR-1 directly from billing data across B2B and B2C with HSN-wise summaries and flags mismatches before filing — cutting monthly compliance effort and keeping the business audit-ready.
Measured against the baseline the audit established — before and after, on the metrics that move the P&L.
Start with a Business Transformation Audit — a structured working session where we map where AI changes your P&L, prioritised by impact.