The $10 Billion Proof Point

Amazon Rufus — the AI shopping assistant embedded directly into Amazon's storefront — has already influenced over $10 billion in purchases. Not through pop-ups or chatbots. Through an agent that actually does things on the page: compares products, applies filters, adds to cart, and guides checkout.

This isn't a chatbot experiment. This is proof that embedded AI agents convert.

The Market Opportunity

The AI shopping assistant market alone is projected to exceed $28 billion. But this isn't just about shopping. Every website with forms, workflows, onboarding, or checkout is leaving money on the table without an embedded agent.

The problem? Building one requires:

• A dedicated AI team
• Custom DOM understanding
• Action execution infrastructure
• Security and sandboxing
• Ongoing maintenance as your site changes

Until now, this was only possible at Amazon's scale.

Why Existing Solutions Fall Short

RAG Chatbots

Traditional chatbots can answer questions but can't do anything. They're read-only. A user says "help me check out" and the chatbot responds with a link. That's not assistance — that's a search engine with a text box.

Screenshot-Based Agents (CUA)

Vision agents take screenshots, analyze pixels, and send click coordinates. They're slow (2-5 seconds per action), expensive (remote VM per session), and fragile (a CSS change breaks everything). They also require sending your users' screens to a third-party server.

Rover: DOM-Native by Design

Rover takes a fundamentally different approach. Instead of screenshots or knowledge bases, it reads the live DOM:

1. Semantic understanding — Rover builds a Smart DOM Tree from your page structure, understanding what each element does (not what it looks like).
2. Minimal action plans — Instead of recording pixel coordinates, Rover plans the fewest possible DOM interactions to accomplish the user's goal.
3. Instant execution — Actions execute in the user's browser tab at native speed. No remote VM, no network round-trips for each click.

Key advantages:

• 10x token efficiency — Smart DOM Trees are 10x smaller than screenshot descriptions
• Sub-second actions — No image processing, no network latency per action
• Zero maintenance — Rover reads the live page, so site changes don't break it
• First-party security — Runs in the user's browser, within their existing session

Benchmark Results

On standardized web automation benchmarks, Rover achieves an 81.39% success rate — outperforming screenshot-based approaches while using a fraction of the compute.

Use Cases

Get Started

Rover is a single script tag. No knowledge base to build. No embeddings to maintain. No screenshots to process.

<script src="https://rover.rtrvr.ai/embed.js" async></script>

Every website deserves its own AI agent. Rover makes it possible without a billion-dollar team.