Cross-Client AI Memory Manager

Developers using multiple AI tools (Claude, Cursor, ChatGPT) have to re-explain context in each one. A lightweight desktop app that syncs memory and preferences across all AI clients, eliminating repetitive context-switching friction for power users.

The surge in developers running three or four AI tools simultaneously is real and recent — Cursor, Claude, and ChatGPT each maintain isolated context by design, and that fragmentation is a daily pain point in 2024-2025 workflows. No clear incumbent owns this space, though some AI clients are building their own memory features (Claude's Projects, ChatGPT Memory) which is the sharpest risk here: platform-level memory features could make a cross-client layer redundant within 12-18 months. The $500-2k/mo band is plausible only as a solo bootstrapped product with low overhead — a small base of power users paying $10-20/month — but the ceiling is genuinely low because this solves friction rather than a core workflow, making it hard to justify higher pricing. The most likely failure mode is that native memory features in the major clients improve fast enough that the integration surface shrinks before the product finds enough paying users to matter.