Developer Tools
Build a paper trading and market simulation platform
Kliv is an AI app builder. Describe your paper trading and market simulation platform, and it builds practice accounts, order rules, loss limits, journals, and mentor review around your rulebook.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t trading software you configure from a fixed menu — it’s an AI app builder that builds software for you.
You describe the app you need in your own words, and Kliv builds it: the data, the rules, the screens, the roles, and the workflows. What you get is a real web app that’s yours, on your own domain, and you can change it later by asking for changes. It isn’t a template or a toy simulator.
On this page, that app is a paper trading and market simulation platform. Kliv builds all kinds of web apps; this one is for training, practice accounts, risk rules, and review.
Why build your own paper trading platform?
Dario trained futures traders and found the same problem in generic paper-trading sites: easy fills, reset buttons, and little memory of what a trainee did across sessions. A simulator that never enforces consequences teaches the wrong habits.
Kliv builds the platform around your desk’s rules. The practice account, order ticket, loss limit, trade journal, and cohort board all read from the same database. The rule that blocks a trade also records why it was blocked.
What fair practice depends on
Realism here is not graphics. It is the records that make the rules hold.
Practice accounts
Each trainee receives a practice stake, such as $50,000, with open positions and a balance computed from fills. Nobody edits the balance directly.
Order tickets
Orders carry side, size, type, and session time. A ticket fills against the next price your feed delivers, not a price that already printed.
Loss limits
Each cohort can have risk rules such as maximum size and a $500 daily stop. Once the stop is hit, the account refuses new tickets until review.
Trade journals
Every fill lands in the trainee’s journal with the rule in force and the note the trainee typed. Trainees read their own journals; mentors can review the cohort.
Cohort board
Standings can score what you value: sessions completed inside the rules first, profit second. The board is computed from session records, not screenshots.
An example: Dario’s futures training desk
Here’s how one training desk might use it. It’s only an example — you would describe your own markets, rules, limits, feed, and review process.
Each trainee starts with the same stake
A trainee begins the cohort with $50,000 in practice capital, the desk rulebook attached, and a session clock running. Her first fill goes straight into the journal.
The daily loss limit stops new orders
After three losing trades, she hits the $500 daily stop. The next ticket is refused, and the account stays locked until Dario reviews it.
The rulebook explains the lock
When she asks why she is locked, the desk agent answers from Dario’s uploaded rulebook and her own fills. It does not answer from another trainee’s data.
Patterns become visible across sessions
Two lockouts, both on Mondays after gap opens, show up in the journal. The app keeps the rows so the mentor and trainee can discuss them.
The final review is based on records
At session thirty, Dario reviews the journal: lockouts, rule compliance, and results. The account closes read-only, so the trainee can reread it but not edit history.
Describe the trading simulator you want
Kliv builds from your description, so the more detail you give, the closer the first version. Spell out the market, feed, account size, risk rules, payments, and review workflow. Here are three to build on:
Futures evaluation desk
Paid seats, limits, journals, and mentor review.
“Build a futures paper-trading platform with $97 evaluation seats sold through checkout, a $50,000 practice stake per trainee, orders filled against my uploaded end-of-day futures feed, a $500 daily loss limit that locks the account, private trade journals, and a mentor review dashboard.”
Classroom stock game
Class sections, portfolios, and pause controls.
“Build a stock-market simulation for my economics classes. Each class section should be its own league, each student should manage a $25,000 practice portfolio, trading should pause during exam weeks, and I need a teacher dashboard to review holdings and journal notes.”
Options practice room
Monthly membership and discipline scoring.
“Build an options paper-trading room where members pay $39 per month, positions mark against the end-of-day option chain I upload, the leaderboard scores rule compliance before profit, and every spread adjustment is saved in a private journal.”
Where the realism comes from
Your feed is the source. The simulator does not bring its own market data. It ingests the feed you already license, or files you upload, on the schedule you set.
A seat can be a product. Dario’s $97 evaluation seat can be a one-time purchase on his own Stripe account. Checkout seats the trainee in the cohort without a separate sync step.
The agent has a boundary. The desk agent can read the rulebook and the asker’s own fills. It does not know tomorrow’s market, and it does not read another trainee’s private journal. Building agents around what they may and may not know is part of the work; the deeper end of that craft covers it in more detail.
Common questions
What exactly is Kliv?
Kliv is an AI app builder that builds custom web apps from a description. For paper trading, it can build practice accounts, order tickets, risk rules, journals, feeds, cohorts, and review screens.
Do I get a real app, or a template?
A real app. The simulator is built around your rulebook, markets, feeds, and cohorts. It is not a generic trading-game template.
Can I change it after it’s built?
Yes. You can change risk rules, account sizes, scoring, review flows, cohort structure, and data imports by asking for changes.
Whose market data does it use?
Yours. You can connect a feed you already license through a server-side function, or upload end-of-day files. The quotes contract stays between you and your data vendor.
Is any real money at risk?
No. Trainees trade practice capital only. The balance is arithmetic, not currency. The real charge, if any, is the seat or membership you sell through checkout.
Can a trainee reset a blown account?
Only if you choose that rule. In Dario’s example, a blown stake remains in the journal, and a second attempt gets a fresh account while the old account stays readable.
Does the agent give trading advice?
No. It answers from the rulebook you provide and the asker’s own fills. It is for explaining rules and records, not predicting markets.
Can mentors see every trainee journal?
Yes, if their role allows it. Trainees see their own journals. Mentors can review the cohort. Those boundaries are data rules, not just hidden buttons.
Can I sell evaluation seats?
Yes. A seat can be a checkout product on your own Stripe account, and purchase can place the trainee into the correct cohort.
Do trainees need Stripe accounts?
No. If you sell seats, trainees pay by card. Payments run through your own Stripe account.
Can scoring favor discipline over profit?
Yes. The cohort board can score completed sessions inside the rules before profit, or use whatever scoring rules your training program needs.
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Build the simulator around your rulebook
Describe the stake, the market feed, the order rules, the loss limits, and the review process in as much detail as you like. Kliv builds the platform that enforces them.