ClaudeFeaturedConversational AI assistant from Anthropic for writing, analysis, coding, and document tasks

Claude is a family of large language model assistants developed by Anthropic, accessible through the claude.ai web interface, mobile apps, and an API. It is designed as a general-purpose conversational assistant capable of drafting and editing text, summarizing and analyzing documents, answering questions, reasoning through problems, and writing and debugging code. Anthropic positions Claude around a design philosophy it describes as "helpful, harmless, and honest," emphasizing safer and more steerable behavior. The models are trained using a method Anthropic calls Constitutional AI, in which the system is guided by a written set of principles (a "constitution") to help it refuse harmful requests and explain its reasoning, reducing reliance on large volumes of human feedback for every safety decision. Over successive releases—including the Claude 3 family (Haiku, Sonnet, and Opus) and later iterations—Anthropic has offered tiers that trade off speed, cost, and capability, with larger models aimed at more complex reasoning and analysis. Claude is notable for supporting large context windows, allowing users to paste or upload lengthy documents, transcripts, or codebases and ask questions across the full material. The chat interface supports file uploads and image understanding in its multimodal models, and a feature called Artifacts lets Claude generate content such as code, documents, or simple apps in a dedicated side panel for iterative editing. Typical users include writers, researchers, analysts, software developers, and knowledge workers who want a capable assistant for long-form text and reasoning tasks. Developers can access Claude through Anthropic's API, and the models are also available via cloud platforms such as Amazon Bedrock and Google Cloud Vertex AI, making it straightforward to embed in applications. In the broader market, Claude competes most directly with OpenAI's ChatGPT and Google's Gemini. It is often praised for the quality of its long-form writing, its handling of long documents, and its relatively cautious, well-structured responses. Like all large language models, it can still produce confident-sounding errors (hallucinations), its knowledge has a training cutoff, and behavior varies across model tiers and over time as the product evolves.