Adept AI licenses its ACT-1 Action Transformer technology to enterprise partners, enabling them to build AI agents that visually control any computer software using natural language commands. Through its partnership model, Adept provides screen-reading AI models, proprietary training datasets, and technical consultation for building custom agentic automation solutions—offering an alternative to traditional RPA platforms for organizations with complex, multi-application workflows.
Adept AI licenses its ACT-1 Action Transformer technology to enterprise partners, enabling them to build AI agents that visually understand and control any computer software using natural language commands. Available exclusively through enterprise partnerships, Adept provides pre-trained agentic models, proprietary training datasets, and dedicated engineering consultation for organizations building custom automation solutions across complex, multi-application workflows.
Adept AI is an enterprise agentic AI licensing platform (custom partnership pricing, typically six-to-seven figures) that provides ACT-1 Action Transformer technology for partners building AI agents capable of visually controlling any software application through natural language commands. Founded in 2022 and backed by $415M in funding, Adept's technology enables organizations to automate complex multi-application workflows without requiring APIs or custom integrations.
The core ACT-1 model uses a transformer architecture purpose-built for action prediction rather than text generation, co-developed by Ashish Vaswani, co-inventor of the original transformer architecture. This approach enables pixel-level visual understanding of any graphical interface—including legacy enterprise software, Citrix-published applications, and remote desktop environments where traditional RPA tools struggle.
In 2024, Adept pivoted from direct enterprise automation services to a technology licensing and partnership model. Several co-founders, including CEO David Luan, moved to Amazon to advance AGI research, while Adept continues licensing its ACT-1 and ACT-2 models, web interaction technology, and proprietary training datasets to enterprise partners.
Adept's partnership approach provides access to pre-trained agentic models, a proprietary actuation layer that translates natural language into precise screen interactions, and multi-step planning frameworks. Partners receive dedicated engineering consultation to customize these components for their specific software environments and industry requirements.
The platform's reinforcement learning capabilities enable continuous adaptation when software interfaces change—addressing the estimated 30-40% maintenance overhead that typically plagues traditional RPA deployments. However, access requires direct enterprise sales engagement with significant upfront investment, and there is no self-service tier, free trial, or public release timeline available.
Ideal partners include Fortune 500 enterprises, software vendors, and system integrators with substantial engineering resources who need to embed agentic AI capabilities into their own products or automate complex workflows spanning multiple enterprise systems.
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Adept AI has successfully pivoted from direct enterprise automation to becoming a critical infrastructure provider for agentic AI development. Their partnership approach allows for deeper customization and industry-specific solutions while leveraging proven web interaction technology. While the barrier to entry is higher due to the enterprise partnership-only model and six-to-seven-figure investment requirements, organizations with complex multi-application workflows and substantial engineering resources may find Adept's visual AI approach superior to traditional RPA platforms for handling legacy systems and novel interfaces.
A purpose-built transformer architecture trained specifically for predicting and executing computer actions rather than generating text. Unlike general LLMs retrofitted for automation, ACT-1 natively understands screen elements, DOM structures, and multi-step action sequences, enabling reliable execution across novel software interfaces.
Pixel-level multimodal analysis that interprets any graphical interface without requiring APIs, accessibility trees, or DOM inspection. This enables automation of legacy enterprise software, Citrix-published applications, and remote desktop environments where traditional RPA tools like UiPath and Blue Prism struggle or fail entirely.
Users describe complex multi-step workflows in plain English, and ACT-1 autonomously plans and executes the required sequence across multiple applications. This eliminates the need for flowchart designers, Python scripting, or RPA studio environments that require specialized training and certifications.
Continuous learning from user demonstrations and feedback loops enables the model to improve over time and adapt when software interfaces change. This addresses the ~30-40% maintenance burden that typically plagues traditional RPA deployments when applications are updated or redesigned.
A specialized actuation layer translates high-level natural language intent into precise screen coordinates, keystrokes, and input commands. This technical infrastructure provides the deterministic execution bridge between probabilistic AI reasoning and the exact input requirements of enterprise software.
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In 2024-2025, Adept transitioned from a direct enterprise automation company to a technology licensing and partnership model. Several co-founders including CEO David Luan, Maxwell Nye, and Augustus Odena joined Amazon to advance AGI research, while Adept continues licensing its ACT-1 and ACT-2 action transformer models, proprietary training datasets, and web interaction technology to enterprise partners building custom agentic AI solutions.
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