Alternatives
Products that do what Limitrum does
Policy kernel for autonomous AI agents
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Mar 2026 · github.com
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Hi everyone, I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts. OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them." Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem. So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level…
Feb 2026 · github.com
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
Sep 2025 · github.com
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Oct 2025 · agentml.dev
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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Your agents. Your servers. Your keys. Your model.
May 2026 · platos.dev
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May 2026 · arden.sh
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Hey Hacker News Community! Mindgard.ai (https://mindgard.ai/) is a way to assess, detect, and respond to cyber-attacks and data leakage against all forms of AI/ML, including LLMs, GenAI and any other AI assets including 3rd party supply chain. It also helps you to discover and learn more about the threats out there for AI. Our current platform version allows you to test different models and variations of attacks. We are Peter and Steve, the founders behind the Mindgard AI Security Labs at mindgard.ai. Our journey began with a simple yet challenging goal: to tackle the…
2024
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Hey HN, We’ve been experimenting with how to make AI agents more deterministic, observable, and production-safe, and that led us to build AgentML — an open-source language for defining agent behavior as state machines, not prompt chains. My co-founder posted before but linked to the project website instead of the repo, so resharing here. AgentML lets you describe your agent’s reasoning and actions as a finite-state model (think SCXML for agents). Each state, transition, and tool call is explicit and machine-verifiable. That means you can: - Reproduce any decision path deterministically -…
Nov 2025 · github.com
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May 2026 · github.com
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