Machan AI looks friendly and simple when you use it — but under the hood, it’s a smart blend of cloud tools, APIs, and creative logic built by a single student developer at C-LORO. This post breaks down how everything actually works and what makes the system tick.
The Base: Firebase and Serverless Thinking
Machan AI runs on a serverless setup using Google Firebase. It’s lightweight, secure, and scalable, which makes it perfect for solo development. Instead of maintaining servers or databases manually, everything runs through managed cloud services. The main Firebase features include:
- Authentication — handles user sign-in securely using email or third-party accounts.
- Cloud Firestore — stores chat sessions, preferences, and test data in real time.
- Cloud Functions — tiny backend scripts that connect the app with external AI APIs to generate responses.
The “AI” Part: Connecting to Real APIs
Machan AI doesn’t run its own large model. Instead, it uses trusted external APIs to process requests and generate replies. This keeps the system fast and flexible, while still delivering useful, human-like answers. The Firebase Cloud Functions act as a secure bridge between users and those APIs — keeping keys safe and requests clean.
Handling Memory and Context
Since Machan AI runs in the browser, it can’t store huge conversation histories. To make chats feel continuous, it uses small context snippets saved in Firestore — just enough to “remember” what you were doing in your current session. It’s simple but effective for light project assistance, coding help, or learning tasks.
Why This Setup Works
Building an AI companion with Firebase proves how much a single developer can achieve using modern cloud tech. It’s secure, scalable, and flexible — and it allows the app to focus more on creativity than infrastructure. Machan AI is still evolving, but its architecture shows that you don’t need a big company to build something meaningful and intelligent.
— Written by the C-LORO Dev Team