DETECTSecurity & safety
Scam Checker App
Sachin Chaurasiya@sachindotcom
A scam checker app that asks 22 questions about a suspicious text message to determine if it is a scam.
Since I got access, I have been playing with Jev, first in the @typesafeai playground to understand how it actually works, what a state is, what a question is, and how they get executed. I got really interested after seeing the results in the playground for the idea I was trying, and then I thought of building an app for the same idea, so I built a scam checker.
The idea is simple: paste a suspicious text message and get a straight answer and the reasons behind it. It is for someone worried and not technical. My parents, probably yours too. They get a message saying their account will be blocked today, and there is nobody to ask at 9pm.
The way it works is that Jev does not write text. It answers typed questions. So my app asks 22 small questions about one message in a single call, and all of them run at the same time in about a second. Things like "does this ask for an OTP?" and "does the link belong to the company it claims to be from?". Then my own code adds them up and decides what to show.
One learning I want to share: I had a question asking whether the message tells the reader to keep it private, and a real bank SMS saying "do not share this code with anyone" scored 0.92. That is literally true, so the question was wrong, not the model. Fixing the wording fixed it.
I have open-sourced the code and also shared my learning in one doc file. The links are in the comments, so check it out, play with it and share your thoughts. And tell me what you are building with Jev.
Related builds
Vectorless RAG with Jev
This project introduces a novel approach to Retrieval Augmented Generation (RAG) that replaces traditional embedding methods with a structured, table-of-contents-based navigation system, significantly improving speed and reducing costs by offloading non-generative tasks to Jev.
