Manufacturing & Production Management
Kliv is an AI app builder. Describe the production planning tool you need — make days, batches, shelves, ready dates, allocations, and yields — and it builds the app.
Just enter your idea into the text box and AI will build it for you
Kliv isn’t a generic planning board — it’s an AI that builds software for you.
You describe the app you need in your own words, and Kliv builds it: the database, calendar, rules, task lists, allocations, and reports. What you get is a real app that’s yours. You can change it later by asking for changes and run it on your own domain or private app URL. It isn’t a template.
On this page, that app is a production planning tool. Kliv builds all kinds of web apps; this one is for production work where capacity, timing, and allocation have to agree.
Some production plans finish in days. Others finish in seasons. A creamery may make wheels today that cannot be sold until next spring, while aging rooms have fixed shelf capacity and milk deliveries keep arriving.
Kliv builds the plan as a database. Make days, batches, wheels, shelves, and orders are rows with relationships, so the calendar can answer how many make days fit, how many wheels the rooms can hold, and how much future stock is already spoken for.
A wheel exists for months before it can be sold. These records keep that time visible.
Each make day pairs recipe and milk on hand: vats, cheese, and expected wheels. A day the deliveries cannot supply fails at entry.
Every batch stores vat day, recipe, and numbered wheels. Each wheel gets a ready date computed from the recipe’s aging time.
Shelf space is a number the database knows. A plan that overfills the caves is impossible to save.
A wholesale order can claim specific wheels by ready date. Two customers cannot claim the same wheel.
Liters in, kilograms out, and wheels that miss grade are recorded per batch, so future plans learn from actual yield.
Here’s how one producer might use it. It’s only an example — you would describe your own recipes, rooms, batches, ready dates, and allocation rules.
Tuesday’s delivery is logged against the farms it came from. The make calendar shows batch 214, twelve vats, and 40 wheels expected.
The day sheet prints recipe, cultures, and targets. Afterward, the batch records 41 wheels and one vat slow to set.
Batch 214 takes assigned shelves in room two. Each wheel’s ready date lands nine months out, computed once from the recipe.
Turning and washing lists are drawn from batch ages every Sunday. A skipped week shows as unfinished work, not as a surprise at grading.
In November, a wholesaler books 30 wheels for spring. The allocation attaches to batch 214’s ready window and reduces what remains available.
When the wheels ship, the invoice can trace back to vat day and the farms in the tank.
Kliv builds from your description, so include recipes, capacities, ready-date rules, batch identifiers, allocation rules, and traceability needs. Here are three examples:
Vats, caves, ready dates, and allocations.
“Build a production planning tool for our creamery with make days scheduled from milk deliveries, batches and numbered wheels, aging-room shelf capacity, recipe-based ready dates, and wholesale orders that allocate wheels by ready date.”
Fermenters as the constraint.
“Build a production planner for our brewery where each brew claims a fermenter for its full schedule, packaging days pull from finished tanks, and the calendar shows tank availability by week.”
Racks, cure times, and launch checks.
“Build a planning tool for our soap workshop with batches on curing racks for four weeks, computed ready dates per recipe, batch labels, and launch dates that check cured stock before going on sale.”
Allocation is counted by the database. An order books wheels from a batch’s ready window, and each wheel can be counted once. Overselling next spring becomes a refused write, not a later apology.
Weekly tasks come from rows. Turning lists, washing schedules, and grading reminders are drawn from batch ages and recipes on a schedule.
Traceability reads the same tables backward. Wheel to batch to vat day to farms is one path through the records, not a reconstruction from binders.
Most internal tools look backward. A production plan faces forward, and it deserves the same database discipline. Internal tools that face forward is where that discipline comes from.
Kliv is an AI that builds custom web apps from a description. For production planning, it builds the calendar, batch records, capacity rules, allocations, task lists, and reports around your process.
A real app. Your recipes, make days, batches, rooms, ready dates, allocations, and yields live in a database built for your production process.
Yes. You can add recipes, rooms, batch fields, capacity rules, task lists, or allocation reports by asking for changes.
Yes. Ready dates are computed when the batch is made, and orders can allocate against those dates.
The batch can be marked down and its allocations exposed for resolution. Affected orders can move to a list with substitute batches suggested.
Yes. Aging time belongs to the recipe, so ready dates are computed per batch while the calendar shows one plan.
Each batch records input and output. Expected yield per recipe can be recalculated from that history.
Yes. Room and shelf capacity can be checked when a batch is scheduled.
Yes. If production is planned in the database, you can trace from a shipped item back to batch, vat day, and suppliers.
Yes. The tool can run on your own domain or a private app URL.
Yes. The code syncs to your own Git repository, and your production records are yours.
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Describe your recipes, deliveries, rooms, batches, ready dates, tasks, and allocation rules in detail. Kliv builds the plan around them.