ContextPort – cross-model memory migration API

Move the same context seamlessly across AI models instead of re-feeding history

Problem

Developers switching between AI models either tolerate clunky ad-hoc context management or lose context entirely; the model layer is commoditizing, but context still cannot travel with the user and project.

Solution

A unified API stores, compresses, and forwards conversation/project context, compatible with OpenRouter and other model aggregators; when users switch models, relevant compressed context is injected automatically to reduce repetition and keep continuity.

Users

Indie developers using multiple LLMs, AI app teams, and teams doing cost-driven multi-model routing

MVP

Minimal write/read context API; auto-compression to fit model context windows; OpenAI and OpenRouter compatible; a simple web panel to view and edit memories; usage and cost stats

Revenue

Usage-based API billing; team plan with shared context spaces and permissions; enterprise self-hosted option

Why now

Model aggregators make switching cheap, but memory remains fragmented; an indie developer can wedge in with a simple API