Autoplay AI

Use your existing intercom tech stack to support your users through a real-time context aware chatbot that can turn proactive.

The first step is adding real-time context - use our sdk to get this up and running in a couple lines of code: https://autoplayai.mintlify.app/recipes/intercom

Quickstart: https://developers.autoplay.ai/sdk/overview

When a user asks a chatbot a question the chatbot has no idea what the user did on the software before asking a question. The chatbot is responding blindly.

User our SDK to build proactive copilots that proactively assist users personalized to their actions and intent - all in a few lines of code.

What Autoplay SDK handles for you

• Real-time events at scale — browser activity becomes normalised, typed payloads your model can read

• Context tooling — buffers, summarisers, and models so volume does not blow your context window

• Golden paths — record ideal journeys with the Autoplay Chrome extension or dashboard

• Workflow completion — per-user mastery, in-progress, and gaps across sessions so suggestions stay relevant

I'm Marie, I founded Autoplay when at my old company we lost a customer simply because they took too long to find a feature we had (hidden under another feature).

Frustrated, they switched back to the old software they were using.

When I delved deeper into the issue of software adoption, I discovered that most people use less than 15% of the software they're paying for.

I frequently encounter companies trying to expand their Product-Led Growth (PLG) motion but are struggling to guide users to utilize their features in the right way for their goals from the moment they press “sign up.”

🤔 Why is this problem becoming more urgent to solve?

As AI makes software easier to build, the key differentiator that will make users stay with your product over another will be how well the product's features align with the user's goals.

Users' attention spans with software are falling, and they want value... immediately.

🛠️ How Autoplay Addresses This:

To tackle this, Autoplay focuses on two main areas:

1. Understanding your UI: We've built a framework to understand your software through video tutorials, documentation, and raw UI.

2. Model Training: We train models to predict user intention, knowledge, and hesitation based on your PostHog session replays.

By combining these two elements, we can tell you what your users are trying to achieve and identify why they are not reaching their goals.

🔮 What's Next?

The next step is to use this data gathered from your session replays to power your software's copilots and agents in real-time, assisting your users at the right moment to help them achieve their goals.

If you use PostHog, getting started with Autoplay is as simple as connecting your PostHog to Autoplay.