System QA
Automatically monitor and assess quality of service chats
What it does
Udesk System QA is an AI-powered quality inspection platform built for enterprise compliance. Powered by large language models and multimodal recognition technology, it delivers full-path compliance control across every customer interaction — automating manual reviews, reducing costs, and boosting efficiency. With multi-Agent collaboration and real-time insights, it helps businesses inspect 100% of interactions and drive continuous service improvement.
Selesaikan masalah inspeksi layanan pelanggan dengan Sistem Inspeksi Kualitas Cerdas Udesk berbasis model besar. Dapatkan cakupan penuh, standarisasi, analisis real-time, dan adaptasi multibahasa untuk kepatuhan bisnis.
Perusahaan ini membutuhkan layanan pelanggan untuk menangani banyak percakapan konsultasi peralatan dan pelaporan kerusakan. Sebelumnya, inspeksi manual hanya mencakup kurang dari 30%, dan proses pemeriksaan kerusakan tidak memiliki standar seragam. Untuk mewujudkan kontrol kualitas penuh, membangun alur tertutup "Inspeksi Otomatis AI - Sampling Manual - Banding Layanan Pelanggan", memantau sikap layanan pelanggan secara bersamaan, dan menstandarkan operasi pemeriksaan kerusakan. Perusahaan ini memiliki bisnis luar negeri yang mencakup banyak wilayah Asia, Eropa dan Amerika, dan layanan pelanggan harus menangani percakapan multibahasa seperti Inggris, Jepang, Jerman, dll. Sebelumnya,…from id.udeskglobal.com
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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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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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