After a decade building ChargeDesk, we've created something that finally bridges the gap between modern LLMs and practical customer engagement. Happy to Help observes visitor behavior with client-side encrypted monitoring and uses AI to intervene at critical moments.

We actually prototyped this four years ago, but shelved it because the AI wasn't capable enough. With recent advancements in LLMs, we've rebuilt it from scratch, and the results have been remarkable - it now handles almost all our customer service and drives significant sales conversions.

Technical implementation: - Real-time client-side behavior analysis (clicks, scrolls, form interactions, mouse movements) with browser-based encryption - Automated RAG construction from your website content - zero manual training required - Model-agnostic architecture that works with any LLM (including your own) - Contextual awareness that detects user friction points, error states, and purchase hesitation - Language and style adaptation system that learns from your existing content

Our most experimental feature: with user permission, the AI can take direct control of the DOM - clicking elements, filling forms, and guiding users through complex processes. This bypasses traditional chatbot limitations by letting the AI directly solve user problems.

We'd love feedback from the HN community, especially on our privacy architecture and real-time interventions.

For those interested in the DOM control beta please drop me an email at james@happytohelp.com