Epoque
The search engine for people, not SEO—reclaiming the web through community-curated intelligence.
The world’s first conversational AI-powered answer engine for real-time, sourced information.
Perplexity AI represents the 2026 gold standard in Retrieval-Augmented Generation (RAG) architecture, bridging the gap between traditional search engines and generative AI. Unlike legacy keyword-based search, Perplexity utilizes a sophisticated orchestration layer that routes queries through a multi-model ecosystem—including their proprietary 'Sonar' models, OpenAI's GPT-4o, and Anthropic's Claude 3.5 Sonnet. The system excels at real-time web indexing, citation-backed response generation, and multi-step reasoning through its 'Pro Search' mode. By mid-2025, Perplexity evolved beyond a simple interface to a full-stack research platform, introducing 'Perplexity Pages' for collaborative content creation and 'Perplexity for Teams' for enterprise knowledge management. Its technical moat lies in its ability to minimize hallucinations by strictly grounding LLM outputs in verified web data, providing a transparent 'source-first' UI that allows users to audit every claim. As the market pivots from link-based discovery to answer-based utility, Perplexity occupies a dominant position as a high-intent research tool for developers, analysts, and knowledge workers globally.
A multi-step reasoning agent that breaks down complex queries, executes multiple web searches, and synthesizes data.
The search engine for people, not SEO—reclaiming the web through community-curated intelligence.
The search engine for AI agents that understands what web pages actually mean.
The privacy-first generative search engine powered by an independent, multi-billion page web index.
The next-generation AI search engine that delivers direct answers and clean content without ads or tracking.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Allows users to switch between GPT-4o, Claude 3.5 Sonnet, and Sonar (Llama-3 based).
Converts research threads into high-fidelity, SEO-optimized web pages with images.
Supports RAG over uploaded documents (PDF, CSV) combined with live web data.
Filters the search index to specific domains (e.g., ArXiv for papers, Reddit for discussions).
Enterprise feature that indexes internal company documents for natural language querying.
Analyzes images via GPT-4o or Claude 3.5 to explain visual data or transcribe text.
Manually aggregating competitor data from dozens of websites is time-consuming.
Registry Updated:2/7/2026
Developers need to find recent fixes for library versions released in the last 24 hours.
Sifting through paywalled or dense academic papers for specific methodology data.