Animam is an AI agent platform designed for websites, enabling automated visitor interaction that goes beyond standard chatbot functionality. The primary function of Animam is to read a website's public pages, understand what the business sells and to whom, and then engage with visitors to perform specific actions. These actions include capturing leads, computing quotes based on the business's own pricing grid, booking real calendar slots, and processing payments through Stripe. The agent operates server-side, meaning it executes tasks using the business's data rather than generating responses from a language model alone, which prevents it from inventing information such as pricing amounts. Key features of Animam include a setup process that requires only pasting a URL, with the agent becoming live in approximately 20 seconds without requiring an account or credit card. The platform offers a WordPress plugin, supports site actions, and enables agentic commerce. It provides a console for agencies to manage white-label bots for multiple clients. Technical capabilities include API access, support for the Model Context Protocol (MCP), and the option to bring your own key (BYOK). Users can configure the agent by talking to it, and the platform logs every conversation and tool call, accessible via API, MCP, or a weekly digest. The agent is hosted in France and is GDPR compliant. Typical use cases for Animam vary by business type. For small businesses and freelancers, the agent answers questions and qualifies leads while the owner works. For WordPress users, it integrates via an official plugin that includes a widget, content sync, and the ability to drive other plugins. Agencies and studios can use the white-label feature to deploy one bot per client, managed through a central console. The workflow begins with the user pasting a URL, after which the agent reads the site and begins interacting with visitors. It captures leads with specific needs and emails, books meetings that are confirmed on both sides, and escalates conversations outside its scope to a human rather than improvising. The agent can also be connected to a user's own AI agent over MCP to refine tools, corpus, and tone based on real conversations.