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Most onboarding gives every user the same tour and waits for them to ask for help. When someone gets stuck, they search through the product, open support, and explain what they already tried. Autoplay gives that journey context. It understands what the user is doing, compares their progress with the onboarding objective your team defines, and offers relevant help when progress stops.

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What changes for the user

A user becomes stalled, Autoplay understands the onboarding objective, the user accepts help, completes the workflow, and can continue learning the product.

Autoplay helps a user move from a stalled workflow to a successful outcome, then continues with the next relevant learning journey.

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What Autoplay enables

Autoplay does not react to every click. It understands live activity in the context of the workflows users should learn and the segment they belong to.

Understand what the user is trying to do

Turn recent product activity into context about what the user is trying to accomplish and what they already attempted.

Know whether they are moving forward

Compare behavior with successful and unsuccessful workflow signals to recognize completion, normal progress, stalls, and unfinished work.

Help when progress stops

Stay quiet while the user progresses, then offer support at a configured moment while keeping the user in control.
This can support a new customer completing initial setup, an existing user returning to an unfinished task, or a more experienced user learning an advanced capability.

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How you build the experience

The four steps describe what your team provides, what Autoplay handles automatically, and how the experience improves over time.

1. Connect live user activity

Connect the session replay provider that already captures what users do inside your product.

2. Define the onboarding objective

Define what each segment should learn, what success looks like, and how the experience will be measured.

3. Add the proactive framework

Configure exploration gates, cooldowns, triggers, and the user-controlled path from a nudge to useful guidance.

4. Build the agent self-improvement loop

Use observed outcomes to improve onboarding and extend the same model into continual adoption.

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Autoplay works with your existing stack

You do not need to replace the tools your team already uses. Each one keeps doing the job it is good at, while Autoplay provides the shared understanding and coordinates when help should be offered. Autoplay MCP sits between these tools as the intelligence layer. Your analytics platform still captures and measures behavior, your support agent still handles the conversation, and your tour provider still delivers visual guidance.

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Beyond initial onboarding

The same workflows can help users keep learning after setup. Your team can define recurring tasks, advanced features, newly released capabilities, and role-specific journeys as additional adoption objectives. Autoplay remembers completed workflows, avoids repeating what users already know, and focuses guidance on unfinished or newly relevant outcomes. Over time, observed completion, stalls, segment performance, and accepted or dismissed offers can help your team refine the experience.

Start with live user activity

See how Autoplay develops an up-to-date understanding of what each user is doing.