DeltaMemory
Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.
DeltaMemory launched on February 26, 2026 with 104 votes, #341 of 16,628 launches that month and more than 95% of that year's launches.
What it does
AI agents are getting smarter, but they still forget everything between sessions. We built DeltaMemory because we kept hitting that wall. Not a vector DB, not RAG, a real memory layer that extracts facts, builds a knowledge graph, and actually learns over time. Rust native. #1 on LoCoMo. 2x faster than Mem0 and other alternatives. 97% cheaper at scale.
DeltaMemory gives enterprise implementation teams a living, source-backed memory of every customer project, and surfaces what needs attention before it becomes a problem.
A living, source-backed record of every customer project. DeltaMemory preserves what was promised, decided, changed, and learned, and surfaces what needs attention before it becomes a problem. Enterprise implementations do not fail because a document is missing. They fail because the real state of a project is scattered across systems and people. When ownership changes or a deal escalates, the truth has to be reconstructed under pressure. A current, source-backed brief that leads with what matters most: open commitments, recent changes, and unresolved blockers. Not a flat dump of the record. DeltaMemory captures explicit and implicit commitments from meetings, chat, email, and tickets. It…from deltamemory.com
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YourMemoryApr 2026 · yourmemoryai.vercel.app · ▲93This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
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YourMemory 2.0Jul 2026 · yourmemoryai.xyz · ▲15Semantic search alone is not enough to capture all connected facts, they will capture the semantically most identical memory only. Tested on HotpotQA public dataset: Vector + BM25 + entity graph: BothFound@5 71.5% Vector + BM25 only: BothFound@5 59.5% Entity graph is the game changer to extract connected facts. More Benchmark result: LongMemEval-S: 84.8% recallAll@5 LoCoMo-10: 59% vs zep cloud 28% What is your approach for connected facts retrieval ?
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