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Professional-grade browser intelligence and document synthesis agent for research-intensive workflows.

The neuro-symbolic engine that bridges the gap between intention and execution across any software interface.

Rabbit's Large Action Model (LAM) represents a fundamental shift in AI architecture, moving beyond Large Language Models that merely predict text to an engine that understands and manipulates software interfaces. Technically, LAM is a neuro-symbolic model designed to model the structure of various software applications and human interactions with them. It operates by observing user interfaces and learning the 'conceptual' layout of buttons, menus, and forms, allowing it to perform complex tasks like booking travel, ordering food, or managing spreadsheets across different platforms without requiring official APIs. In the 2026 market, LAM has evolved from a hardware-exclusive feature into a cross-platform 'Action-as-a-Service' (AaaS) layer. It leverages a proprietary 'Teach Mode' where users can record custom workflows that the model then generalizes across web and mobile environments. This architecture solves the 'API fragmentation' problem, enabling seamless automation between legacy software and modern SaaS tools. By 2026, the model features sub-100ms UI reasoning latency and integrated secure credential management via the Rabbit OS 'Rabbit Hole' portal, positioning it as the primary competitor to traditional RPA and browser-based automation tools.
Rabbit's Large Action Model (LAM) represents a fundamental shift in AI architecture, moving beyond Large Language Models that merely predict text to an engine that understands and manipulates software interfaces.
Explore all tools that specialize in rpa 2.0. This domain focus ensures Rabbit LAM (Large Action Model) delivers optimized results for this specific requirement.
Explore all tools that specialize in automate cross-application workflows. This domain focus ensures Rabbit LAM (Large Action Model) delivers optimized results for this specific requirement.
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A proprietary recording interface that captures UI states and translates user interactions into executable LAM scripts.
Combines deep learning for UI perception with symbolic logic for precise action sequencing.
Creates secure, ephemeral sessions for account interactions without storing raw passwords locally.
Dynamic mapping of UI elements; if a button moves or a website updates, the LAM re-identifies the target based on intent.
Workflow state is maintained across device handoffs (from r1 to desktop to mobile).
Simultaneous processing of vision and audio to understand environmental context during action execution.
A sandbox environment where users can preview LAM actions before they are executed in live environments.
Create a Rabbit account via the Rabbit Hole (web portal).
Link third-party accounts (Spotify, Uber, Amazon) via secure OAuth or session tunneling.
Define the primary 'Persona' for the LAM to adopt (e.g., Professional Assistant).
Enable 'Teach Mode' to record specific custom workflows for non-standard apps.
Configure hardware or software endpoints (r1 device, mobile app, or browser extension).
Set up API keys if using the 2026 Developer Action API.
Execute a 'dry run' in the simulator to verify UI element mapping.
Set budget and execution limits for autonomous transactions.
Deploy agent for real-time monitoring through the dashboard.
Audit execution logs to refine LAM reasoning for complex edge cases.
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Professional-grade browser intelligence and document synthesis agent for research-intensive workflows.

Advanced technical writing synthesis for IEEE-compliant manuscript preparation and academic integrity.

The cross-platform AI teammate with long-term memory and context-aware screen intelligence.