A fair-source chatbot and conversational-form builder: Typebot assembles conversations in a visual graph editor. In a visual graph editor you chain blocks from four categories: bubbles display text, images, video, audio, and embeds; inputs collect data through text fields, email, phone, buttons, picture choices, date pickers, file uploads, and Stripe payments; logic blocks handle conditional branching, variables, URL redirects, A/B testing, and custom JavaScript; integration blocks call webhooks, OpenAI, Google Sheets, Google Analytics, Meta Pixel, Zapier, Make, and Chatwoot. Build once, deploy anywhere: custom domains, WhatsApp, or embedded in any site as a container, popup, or chat bubble through a fast native JS library with no iframe and no external dependencies - plus an HTTP API for executing bots programmatically from any language. Theming covers fonts, colors, roundness, and shadows with custom CSS and reusable templates, and results arrive in real time with drop-off and completion analytics plus CSV export. Two Next.js apps (builder and viewer) self-host via Docker under the Functional Source License, which converts to Apache 2.0 after two years.

Build, deploy, and monitor chatbots and LLM-powered agents on one open-source conversational AI platform: Botpress. Its Studio is a visual development environment: a drag-and-drop canvas arranges conversation logic with nodes for messages, questions, choices, and actions, while a built-in emulator simulates conversations for debugging before anything goes live. Agents ground their answers in a knowledge base assembled from uploaded documents, ingested websites, and past conversations via retrieval-augmented generation, and the LLM layer connects to multiple model providers - GPT-4, Claude, Mistral - with a configurable model strategy. An autonomous engine handles reasoning, tool orchestration, persistent memory across sessions, and sandboxed code execution, and custom code actions in TypeScript extend agents past prebuilt workflows. Over 100 integrations deploy the same bot to WhatsApp, Telegram, Slack, Microsoft Teams, and web chat, and connect it to HubSpot, Zendesk, Zapier, and arbitrary APIs and webhooks. Human handoff, conversation analytics, and quality monitoring cover production operation. Originating in 2017 from a Montreal team, the community edition is developed openly on GitHub.

Companies with privacy and security concerns about piping customer conversations through Intercom or Zendesk run Papercups - open-source live customer chat. The stack is a deliberate strength: an Elixir/Phoenix API over PostgreSQL, with real-time messaging powered by Phoenix Channels and Presence - the same BEAM foundation trusted by Discord and PagerDuty for fault-tolerant, low-latency messaging. Customers see a customizable chat widget that embeds in any site as an HTML snippet, a React component, or even inside React Native apps, with configurable colors, greetings, and away messages. Your team sees a dashboard for managing conversations - close, assign, and prioritize - with Markdown and emoji in replies. The killer workflow is the reply-channel integration: connect Slack or Mattermost and every customer conversation becomes a synced thread your team answers without leaving the tool they already live in, with two-way message syncing handled by webhooks. Email and SMS channels extend intake beyond the widget, an analytics dashboard tracks communication patterns, and the Storytime feature adds real-time screen sharing to watch users navigate while you help them. A documented API supports fully custom chat UIs in Svelte, Flutter, or Vue. MIT-licensed and GDPR-conscious - customer data stays in your PostgreSQL.