Documentation Index
Fetch the complete documentation index at: https://developers.autoplay.ai/llms.txt
Use this file to discover all available pages before exploring further.
🤔 The problem
The problem with reactive customer support chatbots:- They wait to be asked — assuming users will speak up when they’re stuck. They rarely do.
- When users do ask, they’re expected to know how to frame their question correctly. But users don’t know what they don’t know about your platform, and often initiate the conversation in the wrong way.
✅ The solution
What we propose you build with our SDK:- Don’t wait for users to come to your chatbot. Go to them first — with the right help, at the right moment, personalized to what they’ve been doing in your platform.
- Don’t just tell them how to fix it. Show them — by triggering contextual visual guidance through smart tooltips or a browser agent (coming soon).
We stream everything users are doing inside your product — in real time — directly into your AI agent as clean, LLM-ready context. Your customer support copilot sees what they’re clicking, where they’re stuck, and what they’ve mastered — so it can help before someone asks, guide them to the next right step, and stay quiet when it shouldn’t interrupt.
⚡ What Autoplay handles for you
Real-time events at scale
Browser activity becomes normalised, typed payloads your model can read — no noisy raw data.Context tooling
Buffers, summarisers, and typed models keep high event volume from blowing your context window — in dev and production.Golden paths
Record ideal product journeys via the Autoplay Chrome extension or dashboard — so your agent always knows the optimal route through your product.Workflow completion tracking
Per-user mastery, in-progress steps, and gaps across sessions — so suggestions stay relevant and never repeat.Proactive triggers
Define conditions based on real-time activity and fire chat or visual nudges at exactly the right moment — no manual rules engine to build.- Visual guidance (available now) — surface a chat message, quick reply, modal, or in-app tour via your delivery layer.
- Browser agent triggering (coming soon) — fire an autonomous browser agent that completes the task on the user’s behalf.