This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle
What I Built
Freelancers often face scope creep when clients request additional features, revisions, or changes that were not included in the original agreement.
ScopeGuard AI is an AI-powered scope creep detector that helps freelancers compare new client requests against their original project proposal or contract.
Users upload a PDF proposal or contract and enter a new client request. ScopeGuard AI analyzes the request and helps classify it as:
- In scope: The request appears to be covered by the agreement.
- Potentially additional work: The request may go beyond the agreed scope.
- Unclear: More information is needed before making a decision.
The application also provides supporting contract evidence and suggests a professional response that freelancers can adapt before replying to clients.
The target users are freelance developers, designers, independent consultants, and small agencies. A potential business model is a low-cost subscription, subject to validation with real users.
ScopeGuard AI is a decision-support tool, not legal advice.
Demo
🚀 Try the live application: https://scopeguard-ai-556q.onrender.com/
Upload a sample project agreement, enter a new client request, and explore the analysis.
Code
💻 GitHub Repository: https://github.com/aditikshetty/scopeguard-ai
The repository contains the source code for ScopeGuard AI.
How I Built It
I built ScopeGuard AI using Python and Streamlit, with PDF processing and AI-assisted analysis.
The main technologies include:
- Python — Application logic.
- Streamlit — Interactive web interface.
- PyMuPDF — Extracting text from PDF agreements.
- Ollama API — Connecting the application to an AI model.
- Render — Deploying the application online.
The application extracts text from the uploaded agreement, evaluates the client's request against the available contract information, and produces a structured result.
I also worked on checking supporting quotations against the source document to help reduce unsupported claims.
Why Does Open Innovation Matter?
Open innovation makes AI development more accessible to independent developers and small teams.
Open-source tools and open-weight models provide opportunities to experiment with different AI workflows, evaluate model behavior, and explore more affordable deployment options.
For ScopeGuard AI, this matters because freelance proposals and contracts can contain sensitive business information. Exploring local inference and alternative deployment approaches could give users more control over document processing.
This project also helped me understand that building a useful AI application involves more than generating a response. It requires careful document processing, evidence validation, error handling, and a user experience that communicates uncertainty.
What I Learned
Building ScopeGuard AI helped me explore how AI can be applied to a practical business problem.
One important design principle is that the system should not force every request into a definitive answer. Some requests require clarification, and the application should communicate that uncertainty rather than inventing contract terms.
My next goals are to improve automated testing, evaluate classification quality, and gather feedback from freelancers.
I'd love feedback from the community:
Would you use an AI tool to help identify scope creep before agreeing to additional client work? What features would make you trust it?
Top comments (1)
👍good project