Drag and drop designer
Lay out screens, inputs and steps on a canvas. Move a field or a step and the app updates; no code to rewrite.
Platform · App builder
The app builder is where an AI application takes shape: screens, inputs, the steps behind them and what the output looks like. You drag in prebuilt parts, describe rules in plain language, and test with real samples as you go.
Invoice check app: build board
To build2
In progress2
Testing2
Done2
The problem
A distributor in Rajkot wants something simple: upload a supplier invoice, pull out the line items and check them against the purchase order in Tally. The accounts team knows exactly how it should work. The IT team has a queue of bigger jobs, so the request sits on a spreadsheet for a quarter while two people keep checking invoices by hand.
What it gives you
Lay out screens, inputs and steps on a canvas. Move a field or a step and the app updates; no code to rewrite.
Write a rule the way you would say it, such as "flag any line where the rate differs from the PO by more than 2%", and the builder turns it into a step you can read and edit.
Start from parts that already work: file upload, text extraction, a lookup against a master list, an approval button, a summary card.
Send each case down the right path. A matched invoice goes to posting; a mismatch goes to a person with the reason shown.
Start the app when a file lands in a folder or a form is submitted, and decide the exact format of what comes out: a table, a PDF, a message or an entry in another system.
Several people can work on one app, leave notes on a step and run it against sample files at any point, so problems show up before go live.
How it works
An example
The accounts lead builds an app with three parts: upload a supplier invoice, extract line items, compare each line with the open purchase order pulled from Tally. Lines that match on item, quantity and rate are marked ready to post. Anything else lands in a review list with the difference highlighted, and the accountant decides. Before going live, the team runs fifty past invoices through it and checks every result against what was actually posted.
An illustrative example with sample data.
Questions
No. Most apps are built from components and plain language rules. Where a step needs custom code, such as a connector to an older in-house system, the Code Colonies team can write it and drop it in as a component your team then reuses.
You test it as you build. Run real past samples through every version, compare the output with what your team did by hand, and only publish when the results hold up. Each run is logged so you can see what changed between versions.
It can, through the integrations layer, but most teams start with the app preparing entries for a person to approve. Direct posting is a setting you switch on once you trust the results.
Keep going
Platform
Chain AI steps, decisions and hand offs into one flow you can read and change.
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Build the screens people actually use: dashboards, forms, tables and side panels.
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Low code builders make it possible for the people who understand a process to shape the AI that supports it. They do not remove the need for engineers. Some parts of an AI application suit a visual builder well, and others still need code.
Learn moreSee it on your work
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