ChatyTalk Chatbot is a document-based AI assistant for customer service. It uses uploaded FAQs, product information, company documents, text, or Google Docs as its knowledge base, and the assistant answers only from that content to reduce wrong or outdated information. The service is described as powered by Claude and supports natural language understanding and long-text responses.
It is built around a three-step flow: upload documents, connect the assistant, and track activity. Integration options include a REST API with X-API-Key, ready-made widgets for WordPress and Shopify, and an optional WhatsApp channel. All channels can be managed in one project, and conversations are logged per project. The dashboard includes Q&A history, token usage, usage reports, auto-extracted leads, and plan limits, along with a test page for Q&A checking and quality tracking. Lead records can include name, email, phone, and company. The system also supports multiple projects under one organization, with per-project API keys and members.
ChatyTalk is presented for e-commerce customer support, technical support knowledge bases, HR and internal communications, and WhatsApp customer lines. The site says it can answer customer questions on a store with product info, returns, or FAQs, and it can also be used for company questions from internal documents. It is available with a free trial, and plan limits are managed through Stripe subscription billing. Users can control token cost with their own API key.
ChatyTalk Chatbot sits in PulseGate's AI category. It provides real-time, AI-powered chat support on WordPress sites, overcoming cache and firewall issues. It is built as a B2B product for wordPress site owners seeking AI chat support. There is a free tier. It runs on the web, embeddable surfaces, and API.
It is developed by hasanhoca, and it first shipped in 2026. Key capabilities include AI chatbot, multilingual support, and REST API integration. The interface is available in English and Swedish. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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