Suppliers sell liquids by volume — a gallon of agave syrup, a drum of oil, a pint of extract. Recipes and stock counts use weight. Those are different kinds of measurement, and the number that connects them is different for every ingredient: a gallon of syrup and a gallon of oil do not weigh the same. Until now, the only way through was to invent a unit per ingredient and type the factor in yourself — a step that quietly goes wrong at receiving and turns into an argument with a supplier about what the purchase order should have said. Density conversions replace that with one number per product. Set the density, and every conversion between a volume unit and a weight unit is worked out for you, with its arithmetic shown on the row.

A supplier sends you a credit note for goods you are keeping — they overcharged you, or they gave you a volume allowance after the fact. The credit should lower what you owe them and lower what those goods cost you. Until now a vendor credit could only do the first part: the stock stayed on your books at a price you never paid, and the only way to fix its cost was to edit the original purchase order or bill — which erased the credit note from your records. Vendor credit cost impact closes that gap. Every line on a credit now states what it does to the goods, a Reason for credit picks the right behaviour for you, and a Cost Impact panel shows the real numbers — which receipts change, how many units are still on hand versus already sold, and what moves on the books — before you click Authorize.

An email lands from a marketplace: your listing is suspended pending documentation for batch OO-2607-B. Or an auditor picks a batch at random and asks what you tested it for. If your Certificates of Analysis live in an inbox and a shared drive, the next hour is spent searching — and the honest answer to "did anyone check this batch met spec?" is often "probably".

Lot compliance puts that evidence where it belongs: on the batch. File a Certificate of Analysis against the lot it covers, record your own identity check, and enter the lab's numbers so SKU.io judges them against a standard you set. A result outside your limit doesn't just get flagged — it takes the stock off sale.

Plenty of products aren't made in one place. You send ingredients to a co-packer who cooks and blends them, truck the result to a second vendor for filling and pasteurizing, and land the finished cases at a 3PL — three vendors, two hand-offs, one product, and you own the goods the entire way. Until now, modelling that meant inventing the whole structure by hand: a work-in-progress SKU per hand-off, a recipe per stage, lot-tracking flags on every node, contractors, and a production order for each leg — roughly 25 minutes of setup, with several places to get the cost model quietly wrong.

Multi-stage co-manufacturing turns that into one guided flow. Tell SKU.io who does what and what they charge, and it builds the intermediate products, the per-stage recipes, and the vendor terms in a single transaction — then keeps them honest every time you run it.

Your accountant plans cash flow from your accounting file — and until the supplier's invoice arrives, an open purchase order is invisible there. You have committed the money, the goods are on their way, and the books show nothing. For businesses ordering weeks ahead of delivery, that gap can hide a large slice of upcoming spend.

Committed-spend billing closes it. Turn it on and every purchase order you submit posts a bill for its unbilled amount right away, so committed inventory spend appears in your books the moment you commit to it. Each committed bill then looks after itself: it shrinks as real supplier invoices are recorded against the order, and disappears entirely once the order is fully billed.

Your suppliers rarely reach every one of your warehouses in the same number of days. The same vendor might land stock at your main warehouse in two weeks but take six by sea to a warehouse in another region — yet SKU.io applied a single lead time to every destination, so one of those reorder recommendations was always built on the wrong number. Per-warehouse lead times let you set a default lead time on a supplier and then override it for individual warehouses, and demand planning automatically uses the right one for each destination you forecast.

Drop-shipping should be the easiest kind of fulfillment — your supplier ships straight to the customer and you never touch the stock. In practice, an out-of-stock order would quietly backorder against your own warehouse instead of routing to the supplier, and when it didn't drop-ship there was no single place to see why. Drop-ship automation brings the whole flow together: a Drop-ship Status panel that shows exactly why an order will (or won't) route to a supplier, automatic routing of eligible out-of-stock orders, a purchase order created and sent on your behalf, and a clear view of whether that PO actually reached the supplier. No more guessing, no more silent backorders.

Customizing your PDF documents — invoices, purchase orders, packing slips, quotes, credit notes — used to mean wrestling a word-processor-style editor that had its own ideas about your layout. Simple requests like "make the items table span the full page" were surprisingly hard, and anyone comfortable with HTML had to fight the editor's constant reformatting. The new PDF Template Editor replaces all of that with a proper split-pane workspace: your template's HTML on one side, a live PDF preview on the other, and a built-in Template AI assistant that can make layout changes for you from a plain-English instruction — "make the items table full width", "add a Supplier SKU column", "match a clean Stripe-style invoice". Every AI edit is validated, shown as a reviewable diff, and never saved until you say so.

If you plan how much to buy from each supplier every month, that plan probably lives in a spreadsheet — and reconciling it means exporting purchase orders, pivoting them by supplier and month, and eyeballing the result against your budget. By the time you spot an overrun, the money is already spent. Purchasing Targets brings the whole loop into SKU: set a monthly purchase target per supplier, and a live report compares it against your actual purchase orders — with variance, mid-month pacing, and exactly how much room you have left to buy.

Real business relationships are never one person. Your supplier has a sales rep who quotes, an AR specialist who chases invoices, and a shipping coordinator who books freight — but until now, SKU.io gave you a single "contact name" field and left the rest to sticky notes and inbox archaeology. Contacts replaces that flat field with a full contact book on every supplier, customer, and warehouse: unlimited people, each with a role, email, phone, title, and notes, one of them starred as the primary. Contacts show up right in your supplier, customer, and warehouse lists, flow through import and export like any other data in SKU.io, and their personal details are encrypted at rest.