AI Forecasting: Know Exactly What to Buy and When
Stop locking working capital into slow-moving inventory. Our models forecast demand based on your actual order history, supplier lead times, and seasonal cycles.
Why Spreadsheet Forecasting Fails Indian Process Manufacturers
Purchasing raw materials based on simple last-month averages leads to massive stock overages when market demand cools.
Suppliers have fluctuating lead times (7 to 45 days), making manual safety-stock calculations unreliable.
Working capital stays locked in slow-moving grades or gauges while fast-moving items run out unexpectedly.
Spreadsheet formulas become too messy to handle multi-warehouse transfers and seasonal festival surges.
What We Build For Your Supply Chain
Time-series forecasting models trained on your SKU-level sales history and supplier delivery records.
Recommended purchase order quantities that factor in vendor minimum order quantities (MOQ) and lead times.
Seasonal trend analysis that prepares your inventory buffer ahead of regional holidays and monsoon transport slowdowns.
Clean web dashboard with automated export into Tally, Zoho, or your primary accounting system.
What This Forecasting System Does Not Do
- ×Requires at least 6 to 12 months of clean historical invoice and stock transaction records.
- ×Cannot predict sudden government policy shifts, import duty bans, or natural disaster supply shocks.
- ×Model recommendations must be reviewed and approved by your purchase manager before placing purchase orders.
Savings depend on your historical data quality, supplier lead-time consistency, and team usage. We validate these variables on sample data before full deployment.
Frequently Asked Questions
How much historical data do we need to build accurate forecasts?
We recommend at least 12 months of sales and purchase transactions. If you have 6 months of detailed SKU logs, we can start with simpler baseline models and refine accuracy as new data accumulates.
Where does the forecasting model run?
Production models run inside your secure cloud account on AWS, Microsoft Azure, or Google Cloud. We use Google Colab only during initial research experiments and baseline training.
How do you prove that the model works before we commit?
During our 2-week discovery pilot, we run backtesting against your previous quarters. We compare what our model would have recommended against what actually happened to verify stock-out reductions.
What is the expected project cost?
Our two-week discovery pilot costs between Rs 1.5 Lakh and Rs 3 Lakh. Full production implementation typically ranges from Rs 5 Lakh to Rs 10 Lakh depending on SKU count and integration depth.
Ready to cut inventory carrying costs?
Book a free 20-minute call with our engineers. We evaluate your SKU list and outline a 2-week pilot plan.