@Vectorizeio

Makers of Hindsight. Agent memory that lets your agents learn over time. https://xitter.cf/t.co/JkzXgOQg74

Boulder, CO
Joined December 2023
Introducing Hindsight Memlake: agent memory on object storage. 100M memories. Recall under 100 ms p99. Same Hindsight. Up to 47x faster. Up to 26x cheaper.
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NVIDIA Nemotron 3.5 Embed came first on all seven retrieval benchmarks we evaluate Hindsight on. Every recall starts with the embedding model. A better one hands everything downstream a better set of memories. Try it in Hindsight, open source memory for AI agents.
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Document search used to match only the document id. It now searches document text and tells you which fields matched, so the search box finds a document by what it actually says. Knowledge pages and mental models also download as PDF or Markdown.
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Most of this release is reliability work: → deadlocks between consolidation, retain and delete → large graph reads freezing the API → retains replayed after an LLM key was rejected → a failed chunk replacing a stored document → workers exiting cleanly on one SIGTERM
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Banks also get default_observation_scopes, used for every retain that sends none. Set it once and memories about the same subject from different agents consolidate together, with no client change. PATCH an existing document and only the memories whose scopes move get rebuilt.
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Four new providers: → ChatGPT, to run Hindsight on a ChatGPT plan → NVIDIA NIM for embeddings and reranking → ONNX, any cross-encoder reranker in-process → Anthropic Workload Identity Federation, so you can drop the static key
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Hindsight 1.1.0 is out. - Per-document change history - Tag globs for observation scopes - Four new providers - Knowledge page downloads - A long round of reliability work across retain, consolidation and reflect. Everyone on 1.0.x should upgrade. 🧵
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Observations are rebuilt, not versioned. Edit a fact and everything built on it is deleted and rebuilt. That used to leave no trace. Each document now records what changed and which rebuild it caused, so you can work out later why an observation looks the way it does.
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A tag in observation_scopes can now be a glob. [["topic:*"]] groups each memory by whatever topic: tags it carries. That matters when the tags are added during extraction, so the client cannot know them at the time it sends the request.
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our competitors launched new features lately. those show me how far ahead Hindsight is compared to them - one just launched a coding memory benchmark (we did it 3 months ago) - one just launched support for graph (we had it since the beginning) - one just launched today and their main feature (and only one) is to generate skill for the agent (we launched it in April via Mental Models) all our competitors are copying features from us and I couldn't be more flattered November we will launch 2 very big milestones: - cutting down costs and improve speed across every hindsight operation for everyone - reinventing the paradigm for the interaction between agent and memory
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toktok is the first library to have a @typesafeai jev tokenizer github.com/vectorize-io/tokt…
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Vectorize retweeted
Upgraded my OpenClaw to 2026.10.4, and one of the biggest surprises was Hindsight 1.0.0. Turns out @Vectorizeio Hindsight, which I've been using as my agent's long-term memory, now integrates with OpenClaw's native memory provider API. I've been running Hindsight for a while now. I even built my own MCP server for recall and reflect because I wanted my agent to actually make use of those memories. Now OpenClaw can route memory.search and memory.get directly to Hindsight. Which means I can finally start getting rid of some of my hand-rolled memory integration code. lol What I really like is that Hindsight is now treated as a first-class memory provider, instead of relying entirely on custom plugin hooks and MCP tools. As someone who has spent way too much time wiring AI tools together, that's a pretty nice upgrade 😂
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Vectorize retweeted
Guys I'm so Hindsight pilled by @Vectorizeio I have a memory bank for @RuneScape 3 If you played RS3 you'll know it's a huge game, and I'm too busy to read the wiki. So instead I ask questions to my agent, specially about questing and where to get a certain item. And then hindsight saves it all. Hindsight also tracks what I do, as I move on from quest to quest, it kinda creates these decision records, and it even tells me "you were here the last time", or "you got that item that other day ago it's probably in your bank". If you're not using something like this in 2026 bro, this is like having a second brain. I love it. This is super cheeky but I even have an @NousResearch Hermes bot for it! I call it Zaros which is the god of fate and control in Runescape. I want so hard to make an RS3 plugin for this, but I don't have time! Runescape 3 + Hindsight + Hermes is amazing!
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51.3K ⭐ · Global Rank #496 · Hindsight by @Vectorizeio 🧠 Memory for AI agents that learn over time. 🎯 Need your support bot to recall past conversations? 📈 March momentum, a bigger September wave, and +2.9K stars this week. star-history.com/?repos=vect…
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Hermes+Hindsight = OMG
Replying to @HermesAgentTips
Honestly scary at this point. It knows me as well as I do. I attribute a lot of that to Hindsight by @Vectorizeio it took Hermes from really good to OMG!
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Vectorize retweeted
🧰 Trending AI repo: vectorize-io/hindsight Memory for AI agents that learns, not just logs chats. → Retain, recall, reflect: facts become beliefs → ★ 44.6k stars, +445 in a day, MIT Why it matters: agents stop forgetting between sessions. airadar08.github.io/repos/#v…
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Hindsight: memory for AI agents that learns, not just recalls. - Python, MIT, ~50.7k GitHub stars, ~6.1k forks - 288 contributors, main, v1.0.0 - Retain, recall and reflect APIs, Python, TS and Go clients, MCP server Best for: devs building agents that improve over time
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