From what I can tell, it’s essentially a memory layer on top of an LLM: store user facts, retrieve them later, personalize responses. Useful? Sure. Novel? I’m not convinced. We’ve had embeddings + vector search + profile stores for years, and plenty of teams have built similar systems internally.
What’s unclear to me:
What does SuperMemory do better than a well-tuned vector DB + retrieval logic?
Is there anything defensible here beyond UX and branding?
How does it handle memory decay, contradictions, or bad user data at scale?
What’s the real-world latency and cost once you move past demos?
Not trying to dunk on it, if there’s real technical innovation under the hood, I’d like to understand it. But right now it feels like a polished repackaging of known ideas rather than a breakthrough.
Curious to hear from anyone who’s actually integrated it in production or evaluated it seriously.