Agents by Yudex Labs
AI agents that sell, support, and collect
What it does
Agents by Yudex Labs helps businesses deploy AI agents for WhatsApp Business and voice calls. These agents answer customer questions, qualify leads, make and receive calls, manage payments, launch campaigns, and escalate complex conversations to human teams with the appropriate context. Connect your business knowledge, track conversations and leads, and measure results from a single workspace. You can also connect it to Claude or ChatGPT to easily create your agent using the MCP connector.
Crea agentes de IA para ventas, soporte, cobranza y campañas en WhatsApp y por voz. Automatiza conversaciones, llamadas y procesos de negocio.
Despliega agentes de IA para WhatsApp Business y voz. Responden preguntas, califican leads, realizan y reciben llamadas y gestionan cobranzas — de forma autónoma. Conecta Agents con Claude, Codex u otro cliente compatible. Dale una instrucción clara, revisa la configuración propuesta y conserva el control antes de publicar cualquier cambio. ## Objetivo Crea y configura un agente de Agents by Yudex Labs para [soporte, ventas, cobranza u otra categoría]. El objetivo se cumple cuando me muestras la configuración completa, confirmas cómo se conectará ([WhatsApp, voz o ambos]) y esperas mi aprobación antes de aplicar o publicar cualquier cambio. Avísame claramente cada vez que necesites una…from agentsby.yudexlabs.com
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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