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Alisha Catat is a locally run order assistant built for a small print shop in Cisontrol, Rancah, Indonesia. It turns typed, informal orders into a reviewable record: Gemma extracts the details, while the shop’s configured price list and ordinary application code handle matching and arithmetic. The owner checks or edits the result before it is saved.
What Alisha Catat does
The shop handles work such as banners, photo prints, ID cards and invitations. Before the app, prices were kept on a poster, while order details and transactions were written down by hand. Alisha Catat is designed to turn a customer’s message into structured fields: customer name, product or service, dimensions or size, quantity and unit.
For example, the developer gives the Indonesian order “Pak Dedi pesan spanduk 3×1 dua lembar, DP 100rb”—approximately, an order for two 3 × 1 metre banners with a 100,000 IDR down payment. The assistant extracts order information; it does not independently decide what the job costs.
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How an order moves through the app
- Enter the order. The shop worker types an informal customer request, or uses the app’s manual form.
- Extract the details. Gemma identifies the fields from the message. The app then matches the item against the shop’s configured price list.
- Check the confirmation card. The owner can review and correct the extracted details before saving. This matters because an incorrect name, dimension, quantity or unit can change the job and its price.
- Calculate and save. Application code parses down payments and performs decimal arithmetic; after confirmation, the app stores the order in SQLite.
- Use the records. Confirmed data can be used to produce PDF, Excel or image receipts and daily, weekly or monthly sales reports.
This division of responsibility is central to the design: the model interprets informal language, while configured business rules and deterministic code handle the transaction. As developer Joni Ilman Pahmi puts it, “The goal isn’t to replace the shop owner with an AI agent. It’s to reduce repetitive administrative work while keeping the owner in control of every transaction.”
What the early test does—and does not—show
Pahmi reports testing three configurations on five invented sample orders. The samples were not representative shop data, so the results are an early demonstration rather than a general measure of accuracy or speed.
| Configuration | Author-reported extraction result | Author-reported time per order | Context |
|---|---|---|---|
| Gemma 3 4B, longer prompt | 5 of 5 correct | Approximately 37 seconds | Five invented orders; developer’s AMD A8-9600 computer with 8 GB RAM and no dedicated GPU |
| Gemma 3 4B, shorter prompt | 5 of 5 correct | Approximately 23 seconds | Same five-order test and reported hardware |
| Gemma 3 1B, shorter prompt | 4 of 5 correct; the application flagged the miss with a warning | Approximately 11 seconds | Same five-order test and reported hardware |
The results are reported by the project’s author, not an independent benchmark. Five invented examples cannot establish how often the app will handle real orders correctly, and the shorter-prompt timings do not prove that prompt length alone caused the difference. Actual performance can vary with hardware, model, prompt and input. The confirmation step and manual form remain useful safeguards when an extraction is wrong, slow or unavailable.
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What “local” and “offline” mean here
The project uses Ollama with Gemma 3 for local inference, along with SQLite and Drizzle ORM for storage. Its frontend and supporting libraries include Solid-Vue JS, Tailwind CSS, Tabler Icons, Chartist, pdf-lib, ExcelJS and Decimal.js. The developer describes typed-order parsing as running against a locally hosted model without requiring an internet connection.
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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →That is different from saying every input method or connected feature works offline. Browser speech recognition may rely on a remote service, depending on the browser and implementation; the project does not establish that audio is processed locally. Microphone access also generally requires a secure context such as HTTPS or localhost, so a phone connecting to a plain HTTP address on a local network may not be able to use it. Keyboard dictation may be an option depending on the device. In the reported shop setup, the computer has no microphone and the owner mainly types orders.
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Google describes Gemma 3 as an open-weight model family that supports text and image inputs, multilingual use and deployment on devices including laptops and desktops. Its guide to running Gemma with Ollama says variants can run on laptops or small computing devices without a GPU; quantized GGUF versions reduce computing requirements but can also lower output quality. These are platform-level descriptions, not independent confirmation of Alisha Catat’s performance. Google Gemma 3 model card · Google’s guide to running Gemma with Ollama
What the shop owner has said
Pahmi says the owner has tried the app and shares a message from Asep, the shop owner, with permission: “intinamah mantap, aplikasina ringan, mudah di akses bisa offline oge. jeng mempermudah rekap harian sampai bulanan toko saya”. An approximate English translation is: “Overall, it’s great. The application is lightweight, easy to access, works offline too, and makes it easier to recap my shop’s sales from daily to monthly.” That is useful initial feedback, but it does not establish long-term adoption, broad accuracy or a measured amount of time saved.
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- Wall Hanging Design: Kitchen printer with two hanging holes on the bottom support wall mount hanging. Easy to use, save the place. With auto cutter and compatible with several operating systems. Print width: 79.50.5mm; Paper Width: 3 1/8 inch (80mm)
- Wide Compatibility and Reasonable Design: Desktop or wall-mounted type for option, lets you use every space more rationally. The humanized auto-cutter ensures the receipt will not fall to the ground after printing. One-button open cover and large paper warehouse design, easy to use and maintain. Works with MUNBYN 3 1/8 x 203ft thermal paper and Gorilla 3 1/8 x 230 Thermal Paper Receipt Rolls
- Cost-Effective Operation: Supports cash drawer driving, compatible with ESC/POS print commands. The network receipt printer does not need ribbon or ink cartridge, resulting in low operating cost. The printer has the function of overheating protection for long service life. Printing characters with high speed and reliable performance for receipt printing in large shopping malls, supermarkets, retail, hotels, canteens, and restaurants
- Compatibility Notice: The receipt printer is not compatible with Grubhub, Doordash, Square, Chromebook, Uber, or Clover systems. Rongta is a brand dedicated to offering high quality products and good shopping experience for customers
Local inference is not a complete privacy or recovery plan
Keeping typed order text on the shop’s own computer can reduce the need to send it to a remote model provider, according to the developer’s description. It does not, by itself, protect the computer, database or backups, or secure other services connected to the workflow. Access controls, routine backups, error handling and a way to recover data still matter for a shop relying on digital transaction records.
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Check Gemma’s terms before distributing a deployment
Google’s Gemma terms page, last modified April 1, 2026, sets out requirements concerning use restrictions, notices and distribution of Gemma or model derivatives. The project account does not specify whether or how model weights are redistributed, or document a legal review, so it does not establish whether a particular distribution arrangement meets the terms. Anyone planning to distribute a deployment should review the current terms directly: Google Gemma Terms of Use.
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Project details and source
The project and its reported implementation, test results and owner feedback are described by developer Joni Ilman Pahmi in his October 4, 2026 project article. The account is a practical report from an early small-business experiment, not an independent evaluation.
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