Built on your ERP data: sales, stock, SKUs and vendor performance. A short, explained buy list every week. Your buyer approves every line.
Six capabilities that turn a weekly spreadsheet loop into a short list of decisions.
Sales forecast, plans and history rarely agree. The planner reconciles them SKU by SKU and takes the highest signal.
Stock on hand, open purchase orders and goods in transit are subtracted before anything is suggested, so duplicate orders stop at the source.
MOQ, rounding and lead time are applied after netting. Quantities too small to order are held, not forced up.
Open any line to see the derivation in plain language and the exact ERP rows behind each figure.
The best model per SKU is chosen by walk-forward testing on your own history, against a naive baseline it must beat.
Approve, edit or reject each line. An edit is respected exactly. Nothing is ordered automatically.
The AI Procurement Planner is a weekly buying tool for teams that purchase against sales, stock and vendor lead times. You upload exports from your ERP, the planner reconciles demand, nets off everything you already have or have already ordered, applies each vendor's rules, and returns a short buy list with an order quantity per SKU and a flag wherever a human needs to look.
The point is not a bigger report. It is a smaller one. Only the SKUs that need a purchase order or a decision reach the buyer. The rest clear themselves, because the arithmetic says nothing is needed.
It is built by people who have run procurement and shared services, so it follows the way buyers actually work: a weekly cycle, a long tail of SKUs, vendors with minimum order quantities, and a manager who will ask why a quantity was chosen.
Buying too little means stock-outs: lost sales, delayed dispatch, idle production lines, expedited freight and unhappy customers. Buying too much means dead stock: cash locked in the warehouse, markdowns, expiry, and obsolescence when a design or regulation changes.
Both errors are expensive, and both are mostly invisible until they hurt. A stock-out shows up as a missed dispatch. Excess shows up months later in a write-off. By then nobody remembers the line that caused it.
The demand picture is never in one place. Sales history and forecast sit in one report. Stock on hand, open POs and goods in transit sit in others. Production or sales plans come from a third team. Vendor lead time, MOQ and reliability live in master data or in a buyer's memory.
One buyer reconciles all of that by hand, every week, across thousands of SKUs. Sources disagree, and errors stay hidden until something stops.
The planner keeps the same weekly rhythm but moves the reconciliation into a repeatable engine, so the buyer's time goes to exceptions and vendor issues instead of rebuilding the same workbook.
The arithmetic is exact and reconciles to your ERP. That matters when an auditor or a finance head asks how a number was reached.
Here is an illustrative example. Highest plan demand is 1,200. Add 150 for stock awaiting a component. Subtract 400 on hand, 300 on open purchase orders and 200 in transit. Net need is 450. The vendor's MOQ is 250, so the order is 500.
Illustrative example with demo data. Your own figures come from your ERP exports.
Each step carries a plain-language note. The buyer can open the exact ERP records behind any figure, with a query to check them. A zero is explained too: the screen shows whether zero means nothing is needed or the data is missing, which is the difference between a safe skip and a silent gap.
AI predicts and learns. Exact arithmetic places the order.
Accuracy is measured on your own history. A naive baseline is the floor every model must beat, and a live comparison per SKU group is part of the demo. Where history is thin, the system says so and falls back to the simple baseline.
Every decision is recorded. The approved order file carries the system recommendation next to the human decision, so you can see later where buyers overrode the engine and whether they were right.
If you buy against sales, stock and vendor lead times, it applies to you.
| Segment | What gets bought | Typical pressure |
|---|---|---|
| Retail chains | Store and warehouse replenishment across thousands of SKUs | Fashion, grocery, electronics and home ranges |
| Manufacturers | Raw materials, components and packaging before the line runs | Labels, cartons, fasteners, spares |
| Distributors | Wide catalogues from many vendors | Service levels to hold across FMCG, industrial and building supplies |
| Importers | Long lead times and container-sized MOQs | Goods in transit across consumer goods, machinery and chemicals |
| Wholesalers and traders | Fast and slow movers on thin margins | Commodities, hardware, stationery |
| Pharma and healthcare | Expiry and version control on cartons, leaflets and consumables | Distributors, hospitals and manufacturers |
The engine is the same across segments. Vocabulary and parameters change.
We would rather state plainly what is proven and what is not.
| Working today | Planned |
|---|---|
| Multi-source demand reconciliation | Direct ERP API integration (file-based today) |
| Netting, MOQ and exception flags | Safety stock in the engine |
| Per-SKU derivation and source rows | Plant and item-level parameters |
| Forecasting with measured accuracy | Role-based access |
| Approve, edit and reject with audit trail | |
| Browser upload with validation |
Your data stays in your environment. The planner runs on-premise or in your own cloud account as containers on your infrastructure, in two tiers (application and database) that can share existing hosts. There are no external calls on the ordering path. Files are versioned and checksummed, and every upload is downloadable.
Onboarding is configuration and column mapping, not a rebuild. We suggest a discovery call of about 45 minutes, a live walk-through, and a pilot on one product category.
Procurement does not stop at the purchase order. Once a line is approved, vendors confirm and track it through the Vendor Portal, goods arrive through gate-in and warehouse workflows, and invoices can move into AP Automation. The planner sits at the front of that chain.
If your first problem is buying, start here. If it is vendor coordination or receiving, those pages cover the next steps.
We do not ask you to rebuild anything. Pick one category, share your exports, and see the buy list next to what your buyers would have ordered.
Sales, stock, open POs, plans and vendor data for one category, plus a SKU mapping.
Demand reconciled, stock and open POs netted, vendor rules applied, accuracy tested on your history.
Walk the buy list line by line, open the working behind any figure, and compare with your own list.
What buyers, supply chain heads and finance teams ask before trusting a planning tool with purchase decisions.
It is a planning tool that takes your ERP sales, stock, open purchase order and vendor data and produces a short buy list: which SKUs to order, how many, and why. Your buyer approves, edits or rejects every line, so the system recommends and a person decides.
It reconciles several demand sources at once, adds hidden need that no plan shows (such as stock waiting on a component), and explains every quantity line by line with the ERP rows behind it. It sits beside your ERP and works from its exports rather than replacing it.
No. AI forecasts demand and learns which lines your buyers tend to change. The order quantity itself comes from exact rules for netting, MOQ and rounding, so every figure reconciles to your ERP and stands up in an audit. Nothing is ordered without a buyer's approval.
We measure accuracy on your own sales or consumption history using walk-forward testing, and every model has to beat a simple naive baseline. Where history is thin, the system flags it and falls back to the baseline instead of guessing. We do not quote an accuracy figure before testing on your data.
Today through file-based exports: sales, stock, open POs, plans and vendor data that you drag into the browser and that are validated on arrival. Direct ERP API integration is planned, and we will say so plainly when it ships. Onboarding is configuration and column mapping, not a rebuild.
Open purchase orders and in-transit stock are subtracted before any order is suggested. Vendor rules then apply: lead time, MOQ and rounding, and quantities too small to order are held rather than forced up. Vendor reliability flags such as a late vendor reach the buyer with the line.
On-premise or in your own cloud account, running as containers on your infrastructure with an application tier and a database tier that can share existing hosts. There are no external calls on the ordering path, and uploaded files are versioned and checksummed so every upload can be downloaded again.
We need ERP exports (sales, stock, open POs, plans and vendors), a mapping from your product codes to purchased item codes, your parameters (cover days, MOQ, thresholds) and, ideally, one to two years of sales history. It runs on demand data alone without history. A typical start is a discovery call and a pilot on one product category.
Share a few details and we will set up a discovery call of about 45 minutes with a live demo.
Prefer chat? WhatsApp +91 7738829118 or sales@cresolv.com
Book a discovery meeting. We will walk through a live demo and scope a pilot on one product category.