AI Chatbot Platform Introduction

Welcome to WebChatAgent

WebChatAgent is an AI-powered chatbot platform that lets you create intelligent chatbots trained on your own data. Whether you need customer support automation, internal knowledge management, or lead generation — WebChatAgent provides the tools to build, deploy, and manage chatbots with ease.

What this means in practice: you point the platform at your website and upload a few documents, it reads and indexes that content, and within minutes you have a chat bubble on your site that answers visitor questions using your information — not generic internet knowledge.

Key Features

  • AI-Powered Chatbots (RAG) — Train chatbots on your website content, documents, and custom data using Retrieval-Augmented Generation for accurate, context-aware answers.
  • Live Chat with Human Takeover — Seamlessly hand off conversations from the AI to a human agent when needed.
  • Knowledge Gap Detection — Automatically identify questions your chatbot can't answer so you can improve your content.
  • AI Team Wiki — Build an internal knowledge base your team can query using natural language.
  • API Connectors — Connect external data sources to enrich your chatbot's responses with real-time information.
  • MCP Server Support — Extend your chatbot's capabilities with Model Context Protocol servers.
  • WhatsApp Integration — Reach your customers on WhatsApp directly from WebChatAgent.
  • Email Assistant — Connect your mailbox and the AI answers incoming emails, as drafts for review or sent directly.
  • Phone & Voice Channel (Beta) — Let your assistant answer real phone calls in a natural voice, using the same knowledge base as your chat widget.
  • Website Widget — Embed a chat widget on any website — WordPress, Shopify, Wix, Squarespace, or any custom site.
  • Multi-Language Support — Serve customers in their preferred language with automatic language detection.
  • Privacy Controls — Primary platform hosting in Germany, a DPA, documented safeguards and selectable EU-processed models support privacy-conscious deployments. The selected providers and customer configuration still matter.
  • Plan-Based, Not Per-Agent — Every plan includes multiple chatbots, so you scale without paying extra for each agent.

Who Is WebChatAgent For?

WebChatAgent is designed for teams and businesses of all sizes:

  • Small and mid-sized businesses automating support without a dedicated CS team.
  • Mid-market and enterprise teams that prefer self-service onboarding over multi-month sales cycles, with a dedicated Enterprise / white-label tier for regulated and multi-brand setups.
  • Agencies building and reselling chatbot solutions for their clients.
  • E-commerce stores that want to assist shoppers 24/7 with product questions and order information.
  • Support teams aiming to reduce ticket volume and response times.
  • Nonprofits seeking affordable AI tools to engage with their communities.

Plans at a Glance

WebChatAgent scales from a free tier up to enterprise and white-label plans. Moving up a plan raises three things: the number of agents (separate chatbots, for example one for your shop and one for internal docs), the training content the platform indexes from your sites and files (measured in characters, roughly one million characters per 200 to 300 typical web pages), and your monthly message allowance. Paid plans also unlock features like Live Chat, human takeover, API Connectors, WhatsApp, the email assistant, and the phone channel.

You can start on the Free plan with no credit card, and every new account gets a 14-day Premium trial automatically, so you can test the paid features before deciding. For the current plans and what each one includes, see the pricing page.

How messages are counted

"Messages" are the AI answers your bots send; the visitor's questions don't count. Each reply draws from your monthly allowance, which resets at the start of every billing month. Replies from more capable premium models count as more than one message, so a bot on a top-tier model uses your allowance faster than one on a fast, lightweight model. Test messages from the Knowledge Optimizer count too; mining and audits don't.