JARVIS by Staqu Technologies
Turning Existing CCTVs Smarter
What it does
JARVIS by Staqu transforms existing CCTV infrastructure into real-time AI intelligence. Powered by computer vision, deep learning, and an AI layer, it helps businesses improve revenue through customer insights, enhance operations with occupancy and workflow monitoring, and strengthen safety via intrusion, crowd, and anomaly detection. From retail, restaurants, hotels, factories, warehouses & infrastructure to smart cities and stadiums, JARVIS turns passive video feeds into actionable decisions.
Does a similar job
all alternatives →- CAClearcam – Add AI object detection to your IP CCTV cameras2025 · github.com · ▲233
This runs YOLOv8 + bytetrack with Tinygrad detections (depending on user config) are saved and can be sent to the companion iOS app along with a notification, all video processing is done locally, all footage is encrypted before leaving your computer, and the sending notifications + videos part is optional. This uses tinygrad, so it runs well on my apple silicon macs and should be able to run on a lot of hardware (or will be able to when I remove other deps).
- JAJarvis AI – your dedicated concierge for anything2023 · usejarvis.ai · ▲12
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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…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
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