Incident OS
Centralized support operations for modern teams.
What it does
Incident OS is a support operations platform designed for teams that need simpler workflows without the complexity of traditional enterprise tools. The platform centralizes: * ticket management * realtime notifications * operational workflows * SharePoint integration * admin management We're also developing CRM integrations to better connect customer data and support workflows in a single operational layer. Incident OS is built to reduce operational friction and simplify support workflows.
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- IAI am building an open-source incident management platform2024 · github.com · ▲168
I'm building Incidental, an open-source (MIT license) incident management platform. I've been working on it for the past couple of months as a hobby, and now it's at a state where I'm comfortable sharing it. This is also my first open source project. Features: - Custom roles - Custom severities - Integrated with Slack - Web interface Todos: - Custom fields - Custom workflows Website: https://incidental.dev Github: https://github.com/incidentalhq/incidental I'd love to hear your feedback. Thanks!




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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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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai


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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…
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Dev tools · May 2026 · github.com