AI · alternatives · 2026
24 alternatives to ViBo
Memory for AI agents — never costs more than no memory
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Agentmemory▲310Persistent memory for Claude Code, Codex & coding agents
May 2026 · agent-memory.dev · its alternatives →
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Memori▲168Persistent memory from agent trace, not just conversation
May 2026 · memorilabs.ai · its alternatives →
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DeltaMemory▲104Most 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.
Feb 2026 · deltamemory.com · its alternatives →
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YourMemory▲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…
Apr 2026 · yourmemoryai.vercel.app · its alternatives →
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Query Memory▲100One API for all documents your AI agents need
Mar 2026 · querymemory.com · its alternatives →
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Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…
Apr 2026 · github.com · its alternatives →
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Eggshell▲74Local memory for AI agents to reuse work, spend fewer tokens
Sep 2026 · github.com · its alternatives →
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Give AI agents long-term memory. Not vector search or RAG
Dec 2025 · github.com · its alternatives →
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MemoClaw▲6Hey HN, I built MemoClaw, a simple memory service for AI agents. Store and recall memories with semantic search. No registration, no API keys, your wallet address is your identity. How it works: - POST /v1/store → save a memory ($0.001) - POST /v1/recall → semantic search ($0.001) - Payment via x402 protocol (USDC on Base) Why I built this: Every agent framework has its own memory solution, but they're all local or require complex setup. I wanted something like S3 for memories – just call an API and pay for what you use. CLI: `npm install -g memoclaw` Docs:…
Feb 2026 · memoclaw.com · its alternatives →
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Hey HN! I'm Arindam, part of the team behind Memori (https://memori.gibsonai.com/). Memori adds a stateful memory engine to AI agents, enabling them to stay consistent, recall past work, and improve over time. With Memori, agents don’t lose track of multi-step workflows, repeat tool calls, or forget user preferences. Instead, they build up human-like memory that makes them more reliable and efficient across sessions. We’ve also put together demo apps (a personal diary assistant, a research agent, and a travel planner) so you can see memory in action. Current LLMs are stateless…
2025 · github.com · its alternatives →
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Tell MemorySync a fact, reload the page, then ask for it back in your own words. No signup. Every API call shown in cURL, Python and Node.js.
10d ago · memorysync.io · its alternatives →
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An agent that remembers across sessions can keep its memory as curated markdown files, as an auto-mined structured store, or as trained experience.
Aug 2026 · pinglin.tw · its alternatives →
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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Custom AI agents for learning, life, and work
2025 · smartboo.io · its alternatives →
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Open Source Context Infrastructure for AI Agents
May 2026 · ravbyte-ai.github.io · its alternatives →
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Memanto▲5Memory that AI Agents Love ! Free, Open-Source, Functional
Jun 2026 · memanto.ai · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →