Personal Finance & Budgeting
Kliv is an AI app builder. Describe your accounts, assets, lots, imports, sale-matching rules, and reports, and it builds a capital gain tracker from your own rows.
Just enter your idea into the text box and AI will build it for you
Kliv isn’t a finance app with fixed assumptions — 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, import screens, calculations, reports, permissions, and admin views. What you get is a real app that’s yours. You can use it, change it later by asking, and run it on your own accounts. It isn’t a template.
On this page, that app is a capital gain tracker. Kliv builds all kinds of web apps; this is one example.
Brokerage statements often answer their own slice. They do not always answer the household question across RSUs, ESPP purchases, index funds, and a real asset sold years later: what did we actually gain, and which lots produced it?
Kliv builds a lot-level ledger from your own records. Purchases, sales, imports, corporate actions, property improvements, and reports live in a database where each number traces back to the rows that created it.
The tracker keeps the records that support the arithmetic.
Every purchase is a lot with date, quantity, basis, and account. A sale consumes lots by the method you set, and the calculation shows which lots were used.
Splits, mergers, and spinoffs are recorded events that adjust basis. The history can explain what changed and when.
Real assets can keep an improvements ledger. A roof, renovation, or other basis-raising cost lives on the asset record with receipts attached.
Broker statements arrive as CSVs, and each import is kept. A figure on screen can trace back to a line in an imported statement.
An agent can answer from your own rows: holding periods, lots, unrealized positions, and what a hypothetical sale would realize. It computes and cites rows; it does not forecast markets.
Here’s how one household might use it. It’s only an example — you would describe your own accounts, assets, imports, lot rules, and reporting needs.
Stellan imports CSVs from three brokers. Positions reconcile into lots once, so the ledger starts from traceable statement lines.
In March, 240 RSUs vest. The lot appears with vest-day basis, account, and date, ready for future sale matching.
A summer rebalance sells 300 shares. The sale consumes lots by the household’s chosen method, and the realized gain keeps the lots attached.
Their cabin record includes the 2019 roof and receipts. When the cabin sells, the $38,900 gain is calculated from the sale, basis, and improvements ledger.
In April, the realized-gains summary is already there. Their accountant signs in read-only instead of working from a shoebox.
Kliv builds from your description, so the more detail you give, the closer the first version. Include accounts, assets, imports, matching rules, and reports. Here are three to build on:
Lots across every account.
“Build a capital gains tracker with lot-level basis across my Fidelity, Schwab, and employer brokerage accounts. Import CSV statements, show realized and unrealized gains, and let me choose FIFO or specific-lot matching before a sale is recorded.”
Equity compensation and holding periods.
“Build an equity compensation tracker for RSU vests and ESPP purchases. Create a lot for each vest or purchase, track vest-day basis, match sales by my chosen method, and show when each lot becomes long-term.”
Improvements that raise basis.
“Build a property basis tracker for our cabin. Keep purchase price, sale price, closing costs, and an improvements ledger with receipts for the 2019 roof, 2021 deck, and 2023 septic repair, then compute gain at sale.”
Everything traces. Gain traces to lots, lots trace to imports, and imports trace to statement lines. When a figure looks wrong, you inspect a row.
The agent is an arithmetic clerk. It answers from your own rows about holding periods, unrealized gains, and hypothetical sale outcomes. It does arithmetic, not investment forecasting.
Access can be separate. Two household members can each have their own lots, while a shared asset such as a cabin is granted to both. Access is enforced at the row.
An agent you trust near a tax year has to show its work. The AI-apps deep dive covers building agents on owned rows.
Kliv is an AI that builds custom web apps from a description. For capital gains, that can mean imports, lots, calculations, reports, access rules, and an agent that reads your rows.
A real app. Kliv builds the ledger, screens, calculations, and reports for your records. It is not a spreadsheet theme.
Yes. You can ask for changes such as a new import format, a property ledger, a report, or another lot-matching rule.
No. It is a ledger that records what happened and computes numbers from your rows. Decisions stay with you and your accountant.
CSV exports from brokers can import, and each import is kept for traceability. Where an export API exists, a scheduled server-side job can fetch statements.
The matching method is a setting and is shown in the calculation. The app applies the method consistently and keeps the lots attached to each sale.
It can flag rules you define, such as a repurchase inside a window you set, for your accountant’s attention. It flags; it does not adjudicate.
In your app’s database, with access rules per person. The ledger can export whenever you need the record elsewhere.
Yes. You can give a read-only login scoped to the reports or records you want them to see.
Yes. The app can run on your own domain.
Yes. The code syncs to your own Git repository, and your data can be exported.
No. It answers from your rows and does arithmetic. It does not forecast prices or tell you what to buy or sell.
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小規模レストラン向けの予約管理サイトです。
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Describe your accounts, imports, assets, lot rules, improvements, and reports in as much detail as you like. Kliv builds the ledger from your own records.