LinqHive vs Eris.

Linqhive empowers you to create a customizable microsite to consolidate your online presence. Share one link that connects your audience to everything you offer — social media, videos, products, events, and more. Core Features: Add and organize unlimited links Prebuilt templates and branding options Add videos, music, and appointment booking Seamless integration with popular platforms Create and scan QR codes for instant access Responsive design for mobile and tablet Instant publishing and real-time updates Whether you're a creator, business owner, or professional — Linqhive makes it easier to connect with your audience and drive traffic to your content.

Eris brings the power of AI conversation to your iPhone and iPad while keeping your privacy intact. Unlike cloud-based AI assistants, Eris runs entirely on your device using Apple's cutting-edge MLX framework. KEY FEATURES: • 100% Private - All conversations stay on your device • No Internet Required - Chat with AI completely offline • Multiple AI Models - Choose from Llama, Qwen, DeepSeek, and more • Lightning Fast - Optimized for Apple Silicon performance • No Subscriptions - One-time download, use forever • Dark Mode Support - Easy on your eyes • Haptic Feedback - Tactile responses for better interaction SUPPORTED MODELS: • Llama 3.2 (1B, 3B) - Meta's efficient language models • Qwen 2.5 Series - Multilingual capabilities • DeepSeek R1 - Advanced reasoning • Gemma 2, Phi 3.5, Mistral - Various specialized models • Code Models - For programming assistance PRIVACY FIRST: Your conversations never leave your device. No cloud servers, no data collection, no tracking. What you say to Eris stays with Eris. REQUIREMENTS: • iPhone XS/XR or newer (A12 chip required) • iOS 17.6 or later • 2-8GB storage per model Perfect for users who want AI assistance without compromising privacy. Whether you're brainstorming ideas, getting help with code, or just having a conversation, Eris is your private AI companion. Note: First launch includes a one-time model download. Models are stored locally for offline use.