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Mnemosyne

Cognitive memory OS for AI agents (zero LLM calls)

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HN · launched Feb 24, 2026 · 5 upvotes (top 89%) · 0 views

Niche: ai agent memory infrastructure · 350 launches, 16 in the last 7 days ▼ -27% · Explore this niche →

Category and tags

  • Horizontal
  • Data infrastructure
  • Developer
  • AI-native
  • Commercial product

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Could you build this?

Partial While an agent memory API can be prototyped with standard embeddings, designing a full 'cognitive memory OS' with custom non-LLM memory retrieval algorithms and state management requires advanced graph and information retrieval engineering.

What it would actually take: Requires building an embedded high-performance vector/graph hybrid database in Rust or C++, implementing custom graph-based associative memory retrieval and cognitive decay algorithms without relying on LLM summarization. The hard part is achieving deterministic, high-precision retrieval across complex conversational history in single-digit milliseconds, requiring specialized knowledge in information retrieval and memory graph structures.

Discussion

1 comment analyzed.

Competitors mentioned: Mem0, Zep, Cognee, Letta/MemGPT

Concerns raised: LLM API costs at scale ($1,000-3,000/month for 100K memories), Stochastic variance in LLM-based extraction systems

Competitors

Other products that read as similar to this one : 5313 launches clear the similarity bar, closest 8 shown.

Attention rank: #4929 of 5314 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 118 days after the earliest competitor.

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