CrewSpace
CrewSpace — India's answer to OpenAI Operator, at ₹199/month
What it does
Build your own AI agent workforce. Create, configure, and deploy personal AI agents with a visual drag-and-drop workflow builder. CrewSpace is a two-part ecosystem consisting of a Next.js Dashboard (Chatflows) and a Smart Chrome Extension (CrewAgent->CrewSpace). Together, they allow you to create powerful, customizable AI agents that act directly AI sees your webpage context, understands DOM elements, and can autonomously Click, Scroll, Type, Translate, and Navigate on your behalf.
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- CDCrewship – Deploy AI agents to production in one commandFeb 2026 · crewship.dev · ▲11
Hey HN! We built Crewship (https://crewship.dev) because deploying AI agents to production is still unnecessarily painful. If you've built something with CrewAI, LangGraph, or similar frameworks, you know the drill: it works great locally, then you spend days figuring out infrastructure, scaling, monitoring, and artifact management just to get it running for real users. Crewship handles all of that. You add a crewship.toml to your project, run `crewship deploy`, and your agents are live in seconds. It's framework-agnostic — we currently support CrewAI, LangGraph, and LangGraph.js,…
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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.
AI · 18d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
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…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com