Business Tools
Build a supply chain simulation tool
Kliv is an AI app builder. Describe your chain — items, sources, lead times, assumptions, scenarios, stockouts, and freight costs — and it builds the tool.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a packaged planning suite — it’s an AI that builds software for you.
You describe the app you need in plain words, and Kliv builds it: the database, assumption records, scenario functions, comparison screens, reports, and access rules. What you get is a real web app that’s yours, on your own domain, and you can change it later by asking.
On this page, that app is a supply chain simulation tool. Kliv builds all kinds of web apps; planning tools are one example.
Why build your own simulation tool?
Planning arguments often start because assumptions are scattered. One spreadsheet has lead times, another has demand, and the important number may live in a comment.
Kliv builds a tool around your chain. Items, sources, lead times, demand curves, freight costs, scenario runs, and decisions become records, so every run keeps its inputs and outputs together.
Demand and delay as tables
Before you simulate anything, the chain has to be written down.
The item tree
Products by size and color can carry sources and lead times, including items that have sold out before.
Named assumptions
A lead time, demand curve, or freight rate is a row with an author and date. When a run surprises people, you can see the inputs.
The run
A run takes one assumption set, plays out the season, and writes results as rows. Inputs stay with outputs.
The comparison
Runs land in one table, each with stockout counts and freight costs attached. Ocean-only and air top-up can be compared directly.
The decision row
A decision can point at the run it used, so later questions have a link to the evidence.
An example: Ilias’s bicycle brand
Here’s how one business might use it. It’s only an example — you would describe your own items, lead times, assumptions, runs, and comparison rules.
The April question is written down
Dealer preorders close 18% up. Ilias needs to decide whether spring can survive on ocean freight or whether some April inventory should fly.
Assumptions get names and dates
The factory confirms 74 days. Last spring’s demand curve is adjusted for the preorder jump, and every number is stored as a row someone authored.
Six futures are compared
Ocean-only, two air top-up variants, an earlier factory cutover, and two demand curves run by 10:00. Each result shows stockout weeks and freight cost.
The decision points at a run
The team chooses to air-freight M sizes only. The decision row points at run 41, so the reason is visible later.
Actuals improve the next plan
In March, arrivals land against the assumptions. The 74-day lead time turns out to be 79, and that difference is recorded for next winter’s planning.
Describe the decision you need to test
Kliv builds from your description, so include items, assumptions, inputs, scenario rules, outputs, and how runs should be compared.
Bike brand planner
Product tree, lead times, demand assumptions, and freight comparison.
“Build a supply chain simulator for our bicycle brand with products by size and color, versioned lead-time and demand assumptions, scenario runs that compare stockout weeks against freight costs, and a decision record that links to the selected run.”
Container mix decider
Container loading, warehouse space, and seasonal demand.
“Build a simulation tool for our housewares import business that compares container loading mixes against warehouse space and seasonal demand, keeps every scenario run and input set, and reports overflow pallets, stockouts, and landed cost.”
Spare parts stocking
Restocking policies and service levels.
“Build a stocking simulator for our equipment service company that plays min-max and reorder-point policies against two years of breakdown history and shows service level, stockout count, and carrying cost for each policy.”
How the runs stay useful
The math is readable. Scenario logic runs as typed server-side TypeScript, versioned and reviewable. When the logic is wrong, you ask for the function to change.
The data is the data you already have. Sales history, confirmed dates, freight quotes, and product lists can arrive by file upload or manual entry.
Drift can be reported on schedule. A weekly job can compare actual arrivals against the assumptions the current plan still uses and email what changed.
For other internal planning tools, see internal tools that make being wrong affordable.
Common questions
What exactly is Kliv?
Kliv is an AI that builds custom web apps from a description. For supply chain simulation, it builds your data tables, scenario logic, run history, and comparison reports.
Do I get a real app, or a template?
A real app. Kliv builds the database, functions, screens, and reports around your chain.
Can I change it after it’s built?
Yes. Ask for new assumptions, outputs, sweeps, or reports, and Kliv updates the tool.
Does Kliv come with a built-in solver?
No. You describe how your chain behaves. Kliv builds the machinery around your logic: versioned assumptions, recorded runs, and comparable results.
What does “optimization” mean here?
The tool can run and compare the futures you define, and it can sweep ranges such as restock points or cutover dates. The decision remains yours.
How do we know a run can be trusted?
Inputs are stored with outputs, runs can be replayed, and actuals can be compared with the assumptions that predicted them.
What data does it need to start?
A product list, lead times, and some sales or demand history are enough for many first runs. Assumptions can be edited as rows.
Can runs be compared side by side?
Yes. Results can land in one table with the measures you choose, such as stockout count, stockout weeks, freight cost, and carrying cost.
Can I schedule drift reports?
Yes. A scheduled job can compare current actuals with the assumptions behind the active plan.
Can I use my own domain?
Yes. The tool can run on your own domain.
Can I move off Kliv later?
Yes. The app’s source syncs to your own Git repository, and the data is yours to export.
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Run the decision before you make it
Describe your items, lead times, assumptions, costs, and the futures you want compared. Kliv builds the tool that records and compares the runs.