ScopeMate: An Open-Weight AI Assistant to Protect Freelancers from Scope Creep
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle . What I Built ScopeMate is an AI-powered scope and quote assistant designed for freelancers who want to spend less time managing vague client requirements and more time doing the actual work. A simple client re

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 馃捀
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle.
ScopeMate is an AI-powered scope and quote assistant designed for freelancers who want to spend less time managing vague client requirements and more time doing the actual work.
A simple client request can quickly turn into an unclear project, unrealistic expectations, or endless additional requests. ScopeMate helps freelancers turn those rough briefs into structured project proposals with clear deliverables, exclusions, assumptions, milestones, and clarification questions.
Projects can be saved locally in the browser, reopened, edited, and used again when analyzing new client requests.
The people I built this for are freelance developers, designers, writers, and other independent professionals who need a simple way to define work and communicate changes to clients.
I built ScopeMate using Google AI Studio Build mode, React, TypeScript, and a Node.js/Express backend.
The AI features use Google's open-weight Gemma 4 model through a server-side API integration. The model helps interpret client briefs, propose project scopes, and assess new requests against existing requirements.
I kept quote calculations in application code so that financial totals are deterministic and can be edited by the freelancer.
For the first version, I used browser localStorage to keep project history simple, without requiring user accounts or a cloud database.
Freelancers need tools they can adapt to their own workflows rather than being locked into one proprietary AI model or product ecosystem.
Using an open-weight model such as Gemma gives ScopeMate a foundation that developers can inspect, adapt, and potentially run through alternative inference setups as the project evolves.
The current version uses hosted inference, so AI generation requires an internet connection and the relevant client brief is sent to the model provider for processing. I am not claiming that the current application runs its AI entirely locally or guarantees that client data never leaves the device.
The goal is to demonstrate how open-weight AI can support a focused, practical business tool, while keeping important operations such as quote calculations deterministic and giving the freelancer control over the final scope and client communication.
ScopeMate is an early version, and I plan to continue improving it beyond the challenge.
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