Project Difficulty 🚀
Intermediate
Target Audience 🎯
Computer Science Students
Electrical and Computer Engineering Students
Description 📌
This project focuses on developing an AI-powered agent that automates repetitive and complex workflow tasks in a specific domain, such as software development, project management, or cloud operations. The AI agent will be deployed in a sandboxed environment to ensure safety, prevent unintended consequences, and provide controlled automation with strict oversight.
Key Objectives 🔍
Task Identification & Domain Selection: Choose a workflow domain (e.g., DevOps, educational content moderation, research assistance) that benefits from automation while avoiding sensitive applications like finance.
Data Collection & Preprocessing: Gather workflow logs, user interactions, and process documentation in a controlled manner to ensure safety and privacy.
Sandboxed Execution: Deploy the AI agent in a secure, isolated environment to test and validate automation before live system integration.
Integration with Existing Tools: Connect the AI agent with popular workflow tools like JIRA, Slack, Jenkins via APIs.
User Interface & Interaction: Develop a chatbot or dashboard to enable manual overrides, status tracking, and recommendation validation while enforcing safety checks.
Performance & Safety Evaluation: Measure automation effectiveness using KPIs such as time saved, accuracy, efficiency, and adherence to safety policies.
Expected Outcomes 🎯
✅ An AI-driven agent automating repetitive tasks in a sandboxed environment. ✅ A performance & safety evaluation report showcasing efficiency improvements, cost reduction, and risk mitigation. ✅ A deployable prototype demonstrating real-world application and scalability.
Estimated Project Duration ⏳
0-2 months
Team size: 2-5 participants
Hardware / Software Requirements 🛠
The tools below are simply suggestions, you are free to use the tools of your choice.
🔹 Programming Languages
Python
JavaScript (for front-end, if needed)
🔹 APIs & Automation Tools
FastAPI, Flask, Selenium
🔹 Database
PostgreSQL, MongoDB
🔹 Cloud Services
Arm-based servers on AWS, Google Cloud, or Azure
🔹 Sandboxing & Security
Docker-based isolation, SELinux, Kubernetes namespaces
🔹 Hardware
Cloud compute resources (Arm-based AWS, GCP, or Azure)
API access to target workflow tools
Previous Submissions
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AI to Solve Maths Example Sheets at University of Cambridge. (Finley Stirk, Eliyahu Gluschove-Koppel and Ronak De) - https://github.com/egkoppel/example-papers
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AI that interprets user requests, generates circuit descriptions, creates LTSpice ASC code, and iteratively refines circuit designs using a combination of GPT-based language models, a vision analysis module, and LTSpice simulation. (Gijeong Lee, Bill Leoutsakos) - https://github.com/BillLeoutsakosvl346/ElectroNinjaRefined
Resources 📚
Benefits / Prizes 🏆
🎓 Hands-on experience in AI-driven automation with a strong focus on sandboxed execution & safety.
🚀 Exposure to API integration & cloud services, highly relevant for industry roles in AI, automation, and cloud computing.
📃 Standout projects may receive internal referrals for relevant positions at Arm!
🏅 Recognized badge for approved submissions, perfect for listing on your CV or LinkedIn!