🚀 What It Does
OneGo is on a mission. It tirelessly scrapes through files, diving deep into directories from the starting path, and meticulously analyzes their text and content 📄. The secret sauce? An ingenious ML training algorithm 🤖 that can spot sensitive data with pinpoint accuracy based on the context. It distinguishes between:
- ✅ Positives: Exposed data that demands attention.
- ❌ False Positives: The tricky impostors that fool other systems. -❓ Uncertainties: The ones that need a human touch for context-based review.
And it doesn't discriminate when it comes to file formats. Whether it's a humble text file, a complex PDF, a sleek Office document, a mysterious JAR file, a tightly packed compressed archive, a secretive SQLite3 database, or even a whole container 🗃️, OneGo can handle it with ease. Plus, it's got your back with multi-threading support 🚀.
👷♂️ How We Built It
Our dream team of three worked in perfect synergy:
- 👨💻 Michele: ML and AI geek who trained the system to think like a pro.
- 📂 Jeferson: file system crawler developer who gave it the power to explore.
- 🖥️ Loredana: UI/frontend interface maestro who made it beautiful and user-friendly.
🧩 Challenges we ran into
Integrating all these moving parts into one coherent project was no small feat. And then, there were the limitations of our real-world context became a tiny slot of time during the weekend of sleepless hours 🌍. But we love challenges!
🏆 Accomplishments that we're proud of
Educated guesses regarding the classification of the documents the bank provide to test upon.
📚 What we learned
We gained practical skills in ML and AI, learned to work under high-pressure situations, and figured out how to thrive in the fast-paced world of hackathons.
🚀 What's next for OneGo
The beauty of OneGo lies in its modularity. We plan to make it even more powerful by allowing companies to add custom rules that align with their policies. We're envisioning a future where OneGo becomes highly scalable and fully customizable for the masses 🌐
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