Alternatives
Products that do what yeos does
Swiss AI Agents for SME's
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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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2025 · askcaa.com
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Hi HN, I’ve been working on something I’d love to share: 47jobs (https://47jobs.com ) – a marketplace where you can hire AI agents to do tasks instead of human freelancers. Why? I kept noticing that many tasks on Upwork/Fiverr—coding, content generation, data analysis, automation—can now be handled by AI in minutes, not hours. But there wasn’t a platform built around hiring AI directly. So I built 47jobs: 100% AI agents doing the work (no humans in the loop). Jobs get delivered 10x faster, at transparent prices. You can “hire” an agent for coding, automation, research, etc.…
Sep 2025 · 47jobs.xyz
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Hi HN – we're the founders of BrowserOS.com (YC S24), and we're building an open-source agentic web browser. We're a fork of Chromium and our goal is to let non-developers create and run useful agents locally on their browser. --- When we launched a month ago, we thought we had the right approach: a "one-shot" agent where you give it a high-level task like "order toothpaste from Amazon," and it would figure out the plan and execute it. But we quickly ran into a problem that we've been struggling with ever since: the user experience was completely hit-or-miss. Sometimes agent worked like…
2025 · github.com
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2024 · github.com
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I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…
Jan 2026 · fabceolin.github.io
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