Business Tools
Build a commodity price tracking and analysis tool
Kliv is an AI app builder. Describe your commodity price tracking and analysis tool, and it builds price series, recipe cost impact, coverage, alerts, and a decision log.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a market data terminal or a spreadsheet add-on — it’s an AI app builder that builds software for you.
You describe the internal tool you need in your own words, and Kliv builds the real app: the database, the calculations, the screens, the scheduled jobs, and the access rules. You own it, run it on your own accounts, and change it later by asking. It is not a template.
On this page, that app is a commodity price tracker that connects market prices to your own recipes, coverage, alerts, and decisions. Kliv builds all kinds of web apps; this is one.
Why build your own price tracker?
A buyer for a bakery group watches wheat, butter, and cocoa. Market data platforms are built for traders; they know futures curves but not her recipes. A spreadsheet can know the recipes, but it forgets who saw the alert, what was already covered, and why anyone locked six months of butter in May.
Kliv builds the tool where the work happens: one database where price series and bills of materials sit together. When cocoa jumps, the question is not just the new market price. It is what that price does to dark-chocolate rounds, and what decision the team made next.
What the price desk keeps
The tool turns daily numbers into decisions the business can read later.
Price book
Each commodity has a dated series with source and normalized units. Raw quotes and normalized values both stay on the record.
Exposure map
Each SKU recipe links commodities to finished cost, so a wheat move can show impact per unit, per plant, and per week of production.
Coverage and contracts
Locked volumes keep supplier, price, and expiry next to today’s price, so covered and uncovered exposure are visible together.
Alert thresholds
Each commodity can have a trigger line and owner. When it crosses, the alert posts where the team works, with cost impact attached.
Decision log
Every lock, pass, and supplier switch records the price on screen, the reasoning, the volume, and the date.
An example: Birgit’s bakery price desk
Here’s how one buyer might use it. It’s only an example — you would describe your own commodities, recipes, alerts, sources, and decision rules.
Prices arrive before the meeting
A scheduled import loads yesterday’s wheat, butter, sugar, and cocoa closes. Units are normalized and sources are saved before the bakery team starts the day.
A cocoa threshold fires
Cocoa rises 9% and crosses Birgit’s trigger. The Slack alert includes the important part: dark-chocolate rounds are up 1.4 cents per unit at current recipes.
Coverage explains the exposure
The tool shows that 40% of the quarter is already locked at the old price and which SKUs carry the uncovered volume.
The buy decision is recorded
Birgit locks six months at the offered price and writes two sentences explaining why. The log keeps her reasoning beside the price that caused it.
The CFO gets the history
At quarter end, the CFO asks why cocoa costs held while the market rose. The answer is the decision log, sorted by date and tied to the market data.
Describe the price tracker you want
Kliv builds from your description, so include commodities, sources, units, products, alerts, roles, and what a decision record must contain.
Bakery inputs desk
Flour, butter, sugar, and cocoa against recipes.
“Build an internal tracker for our bakery’s flour, butter, sugar, and cocoa prices. Import daily prices from our CSV feed, normalize dollars per tonne and cents per pound, calculate cost impact per SKU and plant, and alert Slack when any input crosses a threshold we set.”
Roastery green-coffee book
Lots, differentials, and landed cost.
“Build a price tracker for our coffee roastery. Track green lots by origin, differential over the C price, freight, import costs, landed cost per bag, contract expiry, and a decision log for when we lock supplier volume.”
Print-shop paper index
Supplier quotes and expired estimate warnings.
“Build a tracker for our print shop’s paper and ink costs by grade and supplier. Keep quote validity dates, warn when a job estimate uses an expired price, and record who approved any estimate based on a manual override.”
Under the graphs
Imports run on a schedule. A server-side function can fill the price book from the data you already use: a subscribed service, a supplier sheet, a broker CSV, or manual entries. Normalization happens on the way in.
Alerts go where the team works. Threshold crossings can post to Slack with cost impact attached. The connection belongs to the app, not to a script on someone’s laptop.
The next analyst can inherit it. The source code syncs both ways with a Git repository your company owns, so the tool can be read, run, and changed later.
A price desk is one internal tool among many that companies rarely find off the shelf. The internal-tools floor of Kliv shows the wider pattern.
Common questions
What exactly is Kliv?
Kliv is an AI app builder that builds custom web apps from a description. For commodity tracking, it builds the internal tool around your prices, products, alerts, and decision records.
Do I get a real app, or a template?
A real app. Kliv builds the database, calculations, screens, imports, and access rules for your case.
Can I change it after it’s built?
Yes. You can add commodities, change alert rules, add reports, or adjust calculations by asking for changes.
Where does the price data come from?
From sources you already have: manual entries, CSV imports, supplier sheets, or a scheduled function calling a data service you subscribe to. Kliv does not bundle market data.
Can it reconcile units and currencies?
Yes. Entries can keep raw quotes and normalized values, so dollars per tonne, cents per pound, and euros per kilo can land in one comparable series.
Can it show impact on our own products?
Yes. Recipes link commodity inputs to SKUs, so a price move can show cost impact by unit, plant, and production volume.
Who can see and change what?
Roles decide it. Buyers may write prices and decisions, plant controllers may read their own exposure, and finance may read everything.
Is this a trading platform?
No. It does not place orders or recommend positions. It records prices, calculates product impact, and keeps the reasoning humans wrote.
Can alerts post to Slack?
Yes. Threshold alerts can post to Slack with the cost impact attached, using a connection authorized for the app.
Can I move off Kliv later?
Yes. The code syncs to your own Git repository, so leaving is a git pull.
Do I need a separate CMS?
No. The tool is its own admin for editing commodities, thresholds, recipes, records, and page text.
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Put prices next to the products they affect
Describe the commodities you watch, the sources you trust, the recipes they feed, and the alerts your team needs. Kliv builds the tracker around those facts.
