Financial Services
Build an AI-powered stock screener
Kliv is an AI app builder. Describe your screening criteria, data feed, saved-run rules, watchlists, and member access, and it builds the stock screener around them.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t an investing platform or data vendor — it’s an AI app builder that builds software for you.
You describe the app you need in plain words, and Kliv builds it: the database, import jobs, screening logic, member screens, permissions, and payment gates. What you get is a real web app that’s yours, live on your own domain, and you can keep changing it by asking for changes.
On this page, that app is an AI-powered stock screener for a club or research group. Kliv builds all kinds of web apps; financial research tools are one example.
Why build your own stock screener?
Retail screeners usually offer the same filters to everyone. An investing club often has its own definitions: payout limits, debt tests, dividend history, and research notes that do not fit a dropdown.
Kliv builds a screener around your criteria. Prices arrive as rows from the feed you subscribe to, rules are named and tracked, runs keep their old results, and members keep private watchlists.
A screen’s moving parts
These records turn a stock-tip habit into a process the club can review.
The price table
Nightly rows from the data feed the club already pays for. Ticker, date, close, dividend, and other fields land by scheduled job.
The criteria
Each rule is a named check with a threshold, implemented as server-side logic. “Quality” becomes a rule the club can inspect.
The runs
Every screen run is saved with its date, universe, criteria version, and survivors. March 3rd’s list stays March 3rd’s list.
Watchlists
Each member has a private watchlist. The database serves each login its own rows and nobody else’s.
The research shelf
Club notes attach to tickers, so the 2024 write-up on a freight carrier is findable when the screen surfaces that company again.
The subscriber door
Outside readers at $37 a month can see run results and commentary. The door checks the membership record before a page is served.
An example: Desmond’s dividend club
Here’s how one club might use it. It’s only an example — you would describe your own criteria, data feed, and access rules.
A rule becomes a named criterion
Desmond writes “payout under 60 percent, 10 years unbroken.” It becomes a named rule with a threshold that members can review.
The data feed imports nightly
A scheduled job pulls prices and dividends after market close from the feed the club already pays for. Runs are logged, and failed imports retry.
The first run is saved
The screen returns 14 survivors. The result is saved with the date and universe, so it can be compared later instead of disappearing into a refreshed page.
Rule changes leave a trail
A member proposes changing the dividend streak from 10 years to 7. The change ships as a commit in the club’s Git repository, and the old runs keep their old results.
Subscribers get access without editing power
Outside readers pay $37 a month for run results and commentary. They cannot edit criteria or see private member watchlists.
Describe what you want to build
Kliv builds from your description, so the more detail you give, the closer the first version. Describe the feed, criteria, saved-run behavior, privacy rules, and subscriber access. Here are three to build on:
Dividend quality screen
Nightly imports and named criteria.
“Build an AI-powered stock screener for our dividend investing club. Import nightly prices and dividends from our paid data feed, flag companies with payout ratio under 60%, debt that could be retired from five years of free cash flow, and at least 10 years of uninterrupted dividend payments.”
Screen run archive
Saved runs for comparison.
“Add a run archive where every screen execution saves its date, criteria version, universe, and surviving tickers, so members can compare old and new rules without recomputing past results.”
Subscriber research desk
Paid readers and private member data.
“Add a $37-a-month subscriber tier. Subscribers can read run results and research notes, but cannot edit criteria, cannot see source code, and cannot view member watchlists.”
The parts that need to be boring
The club’s judgment is the interesting part. The app handles the parts that need to be predictable. Rules are code, and the code syncs both ways with a Git repository the club owns. When a definition changes, the club can quote the commit.
The nightly import is a scheduled job with a log. Watchlists are private because database rules make them private. Subscriber access follows the billing record, so a lapsed subscription closes the door on schedule.
The AI part is an assistant that can read the club’s research shelf and the asking member’s own watchlist. It summarizes what the club has already written about a ticker. It retrieves the club’s judgment; it does not replace it.
A private tool that grew a paying door is a familiar shape: an assistant inside, real gates outside. That shape is the subject of AI apps on Kliv.
Common questions
What exactly is Kliv?
Kliv is an AI app builder that creates custom web apps from a description. For a stock screener, it builds imports, tables, screening logic, saved runs, watchlists, member access, payments, and admin screens.
Do I get a real app, or a template?
A real app. Kliv builds around your data feed, criteria, saved-run requirements, member roles, and access rules.
Can I change it after it’s built?
Yes. You can add criteria, change thresholds, add a subscriber tier, revise imports, or add new dashboards later.
Does it tell members what to buy?
No. It applies criteria the club wrote and shows its work: the rule, threshold, and number that passed or failed. Decisions remain with the club.
Where do the prices come from?
From the market-data feed the club already pays for, pulled nightly by a scheduled job. Kliv is not a data vendor.
Can a subscriber reverse-engineer the screen?
Subscribers can read produced results and commentary, but criteria source code lives in the club’s repository and is not rendered on subscriber pages.
What happens when we change our minds?
Criteria changes are tracked, old runs keep their old results, and comparisons become queries. The club can see how its method changed.
Are watchlists private?
Yes. Watchlists are scoped per member in the database, so one member cannot fetch another member’s list.
Can I charge for access?
Yes. A paid subscriber tier can run through your own Stripe account, with access following the subscription record.
Do subscribers need Stripe accounts?
No. Subscribers just pay by card. Payments run through your Stripe account.
Can I use my own domain?
Yes. The app can run on your own domain and go live as soon as you build it.
Can I move off Kliv later?
Yes. The code syncs to your own Git repository, so leaving is a git pull, not a rebuild.
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Write down your criteria
Describe your data feed, your thresholds, your saved-run rules, and who may see what. Kliv builds the screener around your definitions.
