How to manage long-term memory for AI agents with Synap and Vercel AI SDK

If you’re building AI apps on Vercel, you’ve probably hit this:

as conversations grow → context gets messy → responses degrade

We’ve been working on this problem from the memory layer down.

Built Synap — an agentic context management system that keeps context usable as it scales:
• structured ingestion instead of raw logging
• entity resolution across sessions
• compaction with validation (not blind summarization)

→ 90.2% on LongMemEval (next closest: 71.3%)

It’s designed to sit cleanly in modern app stacks (async, low-latency, non-blocking).

SDK: https://github.com/synap-dev/synap-sdk
Docs: https://docs.maximem.ai
Free tier: https://synap.maximem.ai

Curious how folks here are handling memory in production apps — especially with Vercel AI SDK.