The current wave of artificial intelligence is incredible, but it has a major privacy problem. Most of us are used to sending our data to a distant server and hoping for the best. For developers and professionals handling confidential files, that is often a deal breaker. I wanted to see if we could do better. That is why I am sharing Buddhi AI.
The tagline for the project is simple: Your Data. Your Device. Your Privacy. It is a platform that lets you chat with your documents without ever letting them leave your hardware.
Privacy by Default
Buddhi AI does not use a cloud backend for inference. When you load a document into the app, it stays in your browser. This approach provides a level of security that traditional cloud AI cannot match.
As a developer, I think this "local first" approach is the only way to handle truly sensitive information. We have reached a point where our personal devices are powerful enough to run these models themselves.
The Tech Stack: MediaPipe and LiteRT
I wanted to make sure this was accessible without a complex setup. To achieve this, Buddhi AI is built as a WebAI application. This means there are no installers or environment configurations. You just need a modern web browser.
Here is the stack that makes this possible:
- Google MediaPipe LLM Inference API: This handles the heavy lifting of running the model inside the browser.
- Google LiteRT: Formerly known as TensorFlow Lite, this framework provides the high-performance runtime needed for on-device machine learning.
- Google Gemma 3 2B Instruct: This is the specific model running under the hood. It is small enough to load quickly but smart enough to handle complex document queries.
Zero Installation Required
One of the biggest hurdles for local AI is the setup process. Usually, you have to deal with Python environments, CUDA drivers, or massive downloads. Buddhi AI removes those barriers.
Once you visit the site, the model downloads directly to your browser cache. After that initial step, the app is ready to go. You can even turn off your internet connection and continue chatting with your files. It is a seamless experience that feels like a standard web app but has the power of a local LLM.
My Take on the Future of WebAI
I believe we are moving away from the era where every AI prompt requires a round trip to a data center. Developers are starting to realize that privacy and latency are better handled on the edge. Using tools like LiteRT and Gemma shows that we can build sophisticated tools that respect user boundaries.
I expect to see more "private by design" tools like this in the next year. People are becoming more protective of their data, and as developers, we should build tools that reflect that priority.
Buddhi AI is a fast and private way to use generative AI on your own terms by keeping your documents and your data strictly on your own device.
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