Tiledesk is an open-source platform revolutionizing how companies build sophisticated LLM-enabled chatbots and live chat solutions, balancing advanced automation with crucial data control. It functions as a conversational app development platform, akin to a no-code visual workbench, enabling the creation of complex, multi-step AI bots. A key feature is its seamless human-in-the-loop capability, allowing smooth transitions to human agents with full context, thereby enhancing customer experience. Tiledesk’s multi-channel approach allows users to design responses once, which are then automatically adapted for various platforms like web, WhatsApp, and SMS. The platform utilizes Retrieval Augmented Generation (RAG) with an “agentic” approach, connecting AI agents to internal and external data sources for accurate, verified answers by separating knowledge into distinct repositories. Hybrid search combines keyword and semantic understanding to interpret user intent, even with imprecise language. A defining feature is the self-learning loop, where AI agents continuously improve by analyzing message exchanges and integrating effective human agent solutions. Complex workflows are managed through a no-code visual builder using prompt chains, breaking down logic into smaller, manageable modules. Specialized AI agents can collaborate, handing off tasks and context mid-conversation. Use cases include an e-commerce assistant integrating with platforms like Shopify, AI-powered email ticketing that learns from past resolutions, and a 24-7 scheduling feature. For deployment, Docker Compose is suitable for initial stages, while Kubernetes is recommended for production environments requiring high availability and scalability. Being open-source and offering on-premises deployment provides organizations with complete control over their data and privacy, allowing local LLM integration and vector store control, which is crucial for regulated industries. This deep integration of AI and human agents raises questions about the future role of support staff, potentially shifting them towards becoming expert AI trainers.
