JARVIS vs lamos

CCTV surveillance, the traditional way, is used to stream live video footage on to TV screen monitors. They either need a full-time observation or they are recorded and one can access them later as and when the situation demands so. Now, there is a problem that humans can always make errors while making observations from video surveillance. The operators might unintentionally miss out on crucial suspicious behaviors that can cause possible adversities or mishaps. This is a rather tedious task too. Thus, a simple network of CCTV cameras is just as good as the person sitting behind the ever so many monitors. This is exactly where the use of JARVIS changes the whole game. The app can work all the time and with an accuracy that will miss no suspicious detail. Trained to predict any suspicious behavior based on the body language, the biggest benefit of these systems is that they send real-time alerts to you on your phone or laptop devices synced to it, no matter where you are. Thus, eliminating the need for somebody to keep a constant vigil. Day or night the AI cameras will be there giving you an alert as soon as it finds something anomalous happening. This gives us a lead-time by saving us from going through all video footage for hours finding that one clue.

Lamos is a private, on-device AI assistant for iPhone and iPad. Download a model once, then chat fully offline with no account, no cloud processing, no tracking and no limits. Analyze text, documents, and images with supported models, then tune settings for speed or quality. Your conversations stay on your device. Available models are: - Qwen 3.5 (Alibaba): text + image (vision) - Gemma 4 (Google): text + image (vision) - Ministral (MistralAI): text + image (vision) - Bielik (SpeakLeash): text - LFM 2.5 (Liquid AI): text Use built-in Assistants to improve your interactions with models: - General - Coding Helper - Document Summarizer - Brainstorm Partner Edit any Assistant or create your own. Good to know: At least 4 GB device RAM available - 6 GB or more (even 12 GB) recommended for best performance. App was tested on iPhone 15 and iPad Pro M1.