Alternatives
Products that do what Actx0 does
Memory infrastructure for AI agents.
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The memory layer that decides what's worth remembering
13d ago · skynetlab-cortex.com
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- 18DP
Hello HN, I'm Ali, building Decispher. The problem we're working on is that coding agents repeatedly rediscover context that already exists inside an engineering organization. A developer working on a feature can combine information from previous PRs, Jira tickets, Slack discussions, ownership boundaries, architectural decisions and their own experience. Coding agents usually start with a prompt and a repository, then spend tokens searching for that same context—or miss it entirely. Decispher is a context and memory layer for engineering agents. It currently has three parts: 1) Context…
5d ago
- 19MC
Hi HN, I’ve been building AI agents and copilots, and kept running into a frustrating problem: they don’t fail loudly, they forget things quietly. Users re-explain preferences, agents contradict earlier responses, and context resets without any clear visibility into why. I built Memograph CLI as a debugging tool to analyze conversation transcripts and show: - what the agent forgot - where continuity broke - contradictions and repeated context - estimated token waste due to re-prompting It works locally and supports plain text or JSON transcripts. Example: $ memograph Output: Cognitive Drift…
Feb 2026
- 20DP
devnexus is an open-source cli that gives agents persistent shared memory across repos, sessions, and engineers. It maps out dependencies and relations at the function level, builds a code graph, and writes it into a shared Obsidian vault that every agent reads before writing code. Past decisions are also linked directly to the code they touched, so no one goes down the same dead end twice. Still building it out but I would love to hear any thoughts/feedback
Apr 2026 · github.com
- 21UM
I was frustrated that memory is usually tied to a specific tool. They’re useful inside one session but I have to re-explain the same things when I switch tools or sessions. Furthermore, most agents' memory systems just append to a markdown file and dump the whole thing into context. Eventually, it's full of irrelevant information that wastes tokens. So I built this local memory layer that unifies memory across agents. Instead of a flat file, it builds a structured knowledge graph of "memory notes" inspired by the paper "A-MEM: Agentic Memory for LLM Agents"…
Apr 2026 · github.com
- 22YP
It's an biological inspired decay system for our memories with extended support of temporal reasoning. Created a CLI command to infer knowledge from the context stored in memory system without any token utilization or llm call. It comes with a memory dashboard to monitor and manage your memories it can be extended as audit trail for agents as well !
May 2026
- 23MA
Hello there HN I experimented with agentic coding recently and I felt the need to track more contextual data by project. Also I felt the need to be able to go beyond the 1D chat to communicate with agents. So I created a local document memory, that is discoverable by agents themselves. The CLI is designed to be easy to pick up by agents. It allows humans to collaborate too by reading / searching / editing documents in the store. I have a Mac native GUI in the review process, I hope it will show up in the App Store soon. You can try it easily, instructions here:…
Jun 2026 · metabrain.eu
- 24WM
May 2026 · github.com
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