AI Context Optimizer for Code Editors

Developers waste tokens sending redundant or verbose codebase context to AI coding assistants, inflating costs and slowing interactions. This tool intelligently generates minimal, high-signal context summaries that preserve what AI needs while cutting token usage by 50%+. Target users are developers using Claude, Cursor, Copilot who want faster, cheaper AI assistance.

Token costs are a real and growing pain point as developers run more agentic workflows and longer context windows through Claude and GPT-4o, making context optimization a legitimate problem worth solving now. Cursor has some internal context management, but there's no clear incumbent specifically focused on cross-editor, user-controlled context compression as a standalone layer. The $2k–10k/mo revenue band is plausible for a niche devtool with usage-based or seat pricing, though it likely requires a tight enterprise or power-user wedge to escape the "hobby tool" ceiling. The biggest risk is that model providers themselves compress this problem away — OpenAI, Anthropic, and editor vendors have every incentive to bake smarter context handling directly into their products, which would strand a standalone tool fast.