Anthropic Claude

Claude is your friendly and versatile AI language model that can assist you as a company representative, research assistant, creative partner, or task automator.

Claude is Safe, Clever, and Yours. Built with safety at its core and with industry leading security practices, Claude can be customized to handle complex multi-step instructions and help you achieve your tasks.

Anthropic provides two versions of Claude. Claude and Claude instant. Claude is a state-of-the-art high-performance model. Claude instant is a lighter and much faster option.

Announcing: Claude 2

Anthropic is pleased to announce the launch of Claude 2, showcasing improved performance, longer responses and accessibility via API and a new public-facing beta website, claude.ai.

Claude 2 has demonstrated aptitude in coding, math, and reasoning, scoring 76.5% on the multiple choice section of the Bar exam, a significant improvement from the 73.0% scored by Claude 1.3. When tested against college students applying to graduate school, Claude 2 demonstrated advanced capabilities, scoring above the 90th percentile on the GRE reading and writing exams.

The Claude 2 API for businesses is being offered at the same price as Claude 1.3. Anyone in the US and UK can start using our beta chat experience today.

Users can input up to 100K tokens in each prompt with Claude 2. This means that Claude can process hundreds of pages of technical documentation or even a book. Claude 2 can create longer documents, from memos to letters to stories up to a few thousand tokens, all in one go.

Give Claude a try today and see how it can power up your Hackathon project!

General
Release date	March 14 2023
Author	Anthropic
Type	Natural Language Processing

Start building with Anthropic Claude

To be able to build with this technology you will have to join the waitlist on https://www.anthropic.com/earlyaccess.Learn more about Claude

Claude Libraries

A curated list of libraries to help you build great projects with Claude.

Claude Examples

Agent_Trap_Evals

The problem: agents rarely fail hard questions. They fail chores. They report "backup verified" because the log says success, while the archive is truncated. These false claims slip out during routine work, and a real shell makes them dangerous. What Receipts does: you give it a real task, like checking a backup or triaging a failing build. A control layer plans the work and runs every action in an isolated Vultr sandbox [gVisor pods on VKE]. The sandbox has no secrets, has time and memory caps, and is destroyed after each task. Every command's output, exit code, and files become a receipt. Before any claim reaches you, a verifier checks it against those receipts: did the agent check the layer that matters, or just the easy one? An unsupported claim is blocked and sent back to be verified, or reported as unverified. You get the answer together with its proof. Containment: [demo moment, e.g. the agent runs rm -rf / and the sandbox absorbs it; the host is untouched]. Measured: we score Receipts with agent-trap-evals, an open-source trap set we built before the hackathon from real agent incidents. Verifier off vs. on: [X/Y vs. X/Y caught], [n] false alarms on honest controls. For: platform and DevOps teams putting agents on operational work, where a confident false "done" costs more than a slow answer. Sandboxes like E2B contain actions but don't check claims. Eval tools score offline but don't stop a bad claim at runtime. Receipts does both, live. [Business model; next steps.] All LLM calls use Vultr Serverless Inference.

VOIDLOCK

VOIDLOCK – Containment-First AI Code Execution Platform VOIDLOCK is an AI-powered cybersecurity platform designed to make AI-assisted software development safer, more controlled, and verifiable. It enables developers to submit GitHub repositories and coding tasks, allowing an AI engine to analyse source code and propose necessary modifications. Unlike traditional AI coding agents, VOIDLOCK introduces a deterministic Policy Gate that validates every proposed action before execution, blocking unauthorized operations and potentially dangerous activities. Approved actions are performed inside an isolated Docker sandbox with restricted permissions and resources, keeping execution separated from the developer's main environment. The platform also independently verifies code modifications by running tests rather than blindly trusting AI-generated success reports. Every operation is recorded through a SHA-256 hash-chained receipt system, providing tamper-evident execution records and improved transparency. Developers can monitor execution through a live dashboard, inspect code differences, view test results, stop active operations, and roll back changes when necessary. By combining AI-powered code analysis, deterministic security enforcement, isolated execution, independent verification, and auditable records, VOIDLOCK aims to bring greater security and accountability to AI-driven software development. VOIDLOCK – Contain. Control. Verify

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Web Retrieval Agent: Answers With Proof

Web Retrieval Agent is an AI agent that takes a plain-English question, searches the live web, reads the actual pages and returns only the specific information the user asked for, together with the exact quote that proves it. Most AI search tools write a fluent answer and ask you to trust it. This agent treats the language model as untrusted. It plans targeted search queries, uses Tavily to search and extract full page text, and asks the LLM (gpt-oss-120b on Groq) for a structured answer with verbatim evidence quotes. The server then checks every quote against the real page text and drops any that do not appear. If the answer contains a figure that the quotes do not support, confidence is lowered and the user is warned. If the sources do not contain the answer, the agent says so instead of guessing, and it can retry once with refined queries focused on a likely site. The interface streams the agent's activity live (planning, searching, reading, verifying), then shows the answer, a confidence meter, the proof quotes with source links and every source checked. It is built with Next.js and TypeScript and deployed on Vercel. The LLM client works with any OpenAI-compatible endpoint, so the model can be swapped for an open model served on AMD GPUs.

LifeOS AI — Personal Digital Twin

LifeOS AI is an intelligent personal digital twin designed to transform how people manage their daily lives using artificial intelligence. It learns user-approved preferences and remembers important information while helping users organize tasks and achieve long-term goals. Unlike traditional AI assistants LifeOS AI maintains personalized context to deliver relevant recommendations across conversations. The platform combines persistent memory with AI agents for task planning and knowledge retrieval. Its Personal Memory Engine stores approved information while Retrieval-Augmented Generation (RAG) retrieves relevant context from personal documents. The Intelligent Planning Agent converts goals into actionable steps and prioritizes tasks based on deadlines and preferences. A Goal Tracking Agent monitors progress and suggests adjustments when plans change. LifeOS AI uses large language models to understand natural language and generate contextual responses. Its agent orchestration system coordinates specialized agents to research information and execute approved actions through connected tools. The platform aims to integrate calendars and productivity applications for seamless task management. The project explores AMD GPU acceleration using compatible open-weight models and ROCm with PyTorch where supported. Performance will be evaluated through response latency and task completion rates alongside retrieval quality and resource utilization. Privacy remains a core principle. Users can inspect and delete stored memories and control connected services. The system will distinguish verified information from AI-generated suggestions and request approval before consequential actions. Built with React and Python or Node.js alongside MongoDB and vector search technologies LifeOS AI aims to create a personalized intelligence layer that makes everyday decisions easier and productivity smarter. LifeOS AI — Think Ahead. Act Smarter. Live Better.