u/Weak-Maximum9738

Storing previous information is one thing, but making an AI agent use that information effectively seems much harder.

A good memory system needs to know what to remember, retrieve the right context when needed, and avoid filling the model with outdated or irrelevant information.

For those working with AI memory, what do you think is the hardest part right now: deciding what to remember, retrieval, or keeping context relevant?

Update; i've been thinking more about this, especially how Parallel AI approaches context when AI agents are handling ongoing business workflows. the challenge seems less about storing information and more about giving the agent the right context at the right time.

I'm comparing the both for future sourcing and wanted to hear from people who've actually used both.

Have you noticed any meaningful differences in supplier quality, communication, pricing, verification, or overall reliability?

I'm not looking for a "winner" just interested in real experiences from buyers who have sourced through both. What has your experience been like, and would you choose the same platform again?