SaaS

Yerel Kod Bekçisi (Local Code Guardian)

warningProblem

"Are We Using AI at the Wrong Scale?"

psychologyPotential Solution

A secure, local LLM-based developer assistant that analyzes only the relevant file context instead of sending the entire codebase to cloud-based AI models.

groupTarget Audience

Privacy-focused software companies, engineers working on enterprise projects, and freelance developers with security concerns.

paymentsRevenue Model

Free/limited model for individual users, monthly subscription model (SaaS) for teams and enterprise projects.

Action Plan

Ability to run local models (Ollama integration)

File-based selective context loading (presenting only the active file to AI)

Code security and leakage detection

Advanced IDE plugin (VS Code compatible)

Smart context narrowing for token cost savings

Scoring

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Source: DevTo-Discussopen_in_new

AI Prompt

Build a robust web application using Next.js 14 App Router, TypeScript, and Tailwind CSS. The app should function as a dashboard for a local AI code assistant. Implement a Drizzle ORM setup with PostgreSQL to manage project configurations and code snippets. Create the following: 1) A projects page to list active codebases. 2) A configuration page to manage local LLM endpoints (Ollama). 3) A 'Context Vault' feature allowing users to upload or select specific files from their local machine to be processed locally. Implement full CRUD functionality for project management using Server Actions. Create a secure API route handler to communicate with the local Ollama instance. Ensure the design is professional, dark-themed, and responsive. Include a state management system (Zustand) to handle file selection UI updates. The app must demonstrate a clear architecture for local-first AI interactions, ensuring no full codebase data is uploaded to remote servers.