
LLMs hub for free, while earning from other sources

Integri is a unified platform that provides access to multiple large language models (LLMs), including early-access versions such as GPT-5.2. Designed for users seeking flexible, no-cost interaction with advanced AI capabilities, it supports diverse modalities—text, voice, images, and document analysis—without requiring subscription commitments. The platform targets students, researchers, developers, and general knowledge workers who need reliable, on-demand AI assistance across everyday tasks.
Integri operates in a public beta phase, offering core functionality at no cost while incorporating optional enhancements via subscription. During this testing period, personalized news delivery is available in select countries. The platform’s infrastructure is sustained through an alternative revenue model that does not rely on user payments for basic access.
Users interact with Integri through a web interface hosted at integri.app. Upon arrival, guests can immediately begin using core AI functions—including text-based chat, multi-chat management, agent workflows, image generation, and PDF analysis—without registration. Each session is locally tracked, and chat history is persistently stored and retrievable via the History page. The platform routes user inputs to appropriate underlying LLMs based on selected mode (e.g., GPT-5.2 for conversational tasks, specialized models for image synthesis).
The backend architecture decouples free-tier access from monetization: operational costs are covered through non-subscription revenue streams, allowing unrestricted use of foundational features. Subscription access extends capabilities—for example, enabling higher usage quotas, priority processing, or advanced analysis tools—but is not required for baseline functionality. Cookie preferences are managed explicitly during first visit, with clear distinction between essential (required for operation) and optional (for analytics or UX enhancement) categories.
Integri supports practical, real-world applications across domains: students can analyze academic PDFs and summarize research; professionals can generate draft content or visualize concepts via image synthesis; journalists and analysts may leverage the personalized news feed (where available) for contextual updates; and developers can experiment with multimodal LLM integrations without provisioning infrastructure. Its guest-first design lowers barriers to entry, while persistent history and multi-chat support improve workflow continuity. The platform’s modular interface—featuring dedicated sections for chat, agents, image generation, and document interaction—enables task-specific focus without context switching.