A Large Action Model designed to bridge the gap between human intent and software execution.
Adept ACT-1 (Action Transformer) represents a fundamental shift in AI capability, moving beyond textual generation into direct digital agency. Unlike standard LLMs that predict the next word, ACT-1 is trained on interactions with software, effectively treating the Graphical User Interface (GUI) as a sequence of observations and actions. In the 2026 market, ACT-1 serves as a high-level orchestration layer that allows users to execute complex, multi-step workflows across disparate software tools—such as Salesforce, Excel, and custom web apps—using only natural language. Technically, it functions by mapping pixels and DOM elements to semantic actions, enabling it to 'see' a screen like a human and 'click' or 'type' accordingly. Following the strategic licensing deal with Amazon in late 2024, the technology has evolved into a robust enterprise-grade solution, prioritizing security sandboxing and human-in-the-loop oversight. It is positioned as the primary alternative to traditional, brittle RPA, providing a flexible intelligence that can handle UI changes without breaking scripts.
Adept ACT-1 (Action Transformer) represents a fundamental shift in AI capability, moving beyond textual generation into direct digital agency.
Explore all tools that specialize in automate cross-application workflows. This domain focus ensures Adept ACT-1 delivers optimized results for this specific requirement.
Explore all tools that specialize in ui automation. This domain focus ensures Adept ACT-1 delivers optimized results for this specific requirement.
Uses a vision-language transformer to map raw pixels to underlying software components without requiring a dedicated API for every button.
A planning module that breaks down a complex goal into 10+ sub-tasks and executes them sequentially while maintaining state.
Maintains data context when switching between tabs (e.g., copying a lead from LinkedIn and formatting it correctly in Salesforce).
Uncertainty-based pausing that prompts users to confirm actions when UI confidence falls below a set threshold.
Identifies when a software interaction fails (e.g., a page doesn't load) and attempts alternative navigation paths.
Automatically masks PII (Personally Identifiable Information) before the UI screenshot is processed by the cloud model.
Learns frequent user workflows and converts them into repeatable 'one-click' natural language commands.
Request access through the Adept enterprise portal or AWS Bedrock (post-partnership integration).
Initialize the Adept browser extension or desktop overlay within a secure sandbox environment.
Authenticate the AI agent across required software platforms (CRM, ERP, etc.).
Conduct environment calibration to ensure the model recognizes custom UI elements.
Define security boundaries and data-redaction rules for sensitive information.
Map initial workflows using the 'Record and Refine' training mode.
Configure human-in-the-loop triggers for high-stakes action validation.
Deploy the ACT-1 model to a limited set of pilot users.
Monitor action accuracy through the Adept Governance Dashboard.
Scale execution across the organization with centralized policy management.
All Set
Ready to go
Verified feedback from other users.
"Users praise its ability to handle 'invisible' UI tasks that standard automation tools fail on, though latency in multi-step workflows is noted as a trade-off for its intelligence."
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