Caura

Building the memory layer for the hyper-agent generation. Governed shared memory for AI agent fleets. Open source and

[Caura @CauraAI]

@decklabs_io that said, the older plan will not be deleted and the issue will probably be floated to the user as an insight to observe by the system's self-evolving scheduled processed.

[Caura @CauraAI]

Governed shared memory for AI agent fleets.

Open source. Apache 2.0. Hybrid retrieval, contradiction detection, audit trail, 12 MCP tools.

Five minutes from `git clone` to a running stack — on your laptop, your cluster, or your air-gapped network.

[Caura @CauraAI]

@decklabs_io @decklabs_io great question. If two agents propose contradicting plans to the exact same goal and only if they both decided to save their plan into memclaw the system will mark it as contradicting and will have the newer plan to supersede the older one.

[Caura @CauraAI]

@sohith_uv @nikos1 @composio @nebiusai Actions gave agents utility. Memory gives them continuity. Shared, governed memory is what lets them scale.
https://t.co/frje58v7oj

[Caura @CauraAI]

@cleartechtoday Interesting framing. We'd argue Layer 5 becomes less about context windows and more about governed memory shared across agents, tools, and teams.
https://t.co/frje58v7oj

[Caura @CauraAI]

@TechAIDailyNews Persistent agents are only as useful as the memory layer behind them. As enterprises move to always-on agents, governance and memory consistency become critical.

[Caura @CauraAI]

@RYJOXTech The future isn't just agents. It's agents with memory, accountability, and shared context.
https://t.co/frje58v7oj 🚀

[Caura @CauraAI]

@PeterJ_Medina Agreed. The next challenge isn't just remembering-it's ensuring multiple agents can share memory safely and consistently.
https://t.co/frje58v7oj

[Caura @CauraAI]

@gippp69 Super cool. We natively connect to any Hermes agent and let him state-of-the-art memory, read about it: https://t.co/UUvy7eXTD7

[Caura @CauraAI]

@ericosiu The missing box in most AI org charts is governed memory. Agent fleets scale only when they can share context safely.
https://t.co/frje58v7oj

[Caura @CauraAI]

@0xMovez The future isn't one agent. It's fleets of agents sharing trusted memory.
That's the problem we're solving at Caura. https://t.co/frje58v7oj 🚀

[Caura @CauraAI]

@v0Architect Agreed. If it's not easy to start, nothing else matters.

[Caura @CauraAI]

@dariocosta_base Absolutely. Speed helps adoption, but consistency and error containment are what make large-scale agent fleets viable.

[Caura @CauraAI]

@virtuals_daily Agreed. The goal is to catch conflicting information before it propagates through the fleet, helping agents maintain a more reliable and consistent shared memory state.

[Caura @CauraAI]

@JfkWhitlam Thanks for the reference - cool model to run agents on

[Caura @CauraAI]

We married Claude and ChatGPT.
MemClaw was the bestman.
Tell one. The other remembers.

[Caura @CauraAI]

@karpathy's loop is the right shape.
But when each agent loops alone, every iteration starts from zero. Nothing compounds across the fleet.
Shared memory is the missing operator — what turns N parallel loops into one compounding system.
https://t.co/ycu1KUDEcQ

[Caura @CauraAI]

@decklabs_io @dariocosta_base Exactly. Multi-agent workflows are where consistency checks become especially important as context gets shared and reused.

[Caura @CauraAI]

@base_daily_eth Exactly. Detection is important, but being able to trace how agents arrived at conflicting conclusions is what makes shared memory trustworthy.

[Caura @CauraAI]

@dariocosta_base @decklabs_io dario - sorry (:

[Caura @CauraAI]

@dariocosta_base @decklabs_io Hey Darion, detection runs per write at realtime and than again on a scheduled process for colliding agents and more thorough contradiction analysis. hope it helps

[Caura @CauraAI]

@gippp69 You're welcome to visit https://t.co/oh3vrYfNhy and learn how we made the memory a live metabolism by implementing self-cleaning and self-evolving mechanism