Adept

Adept is an Artificial Intelligence (AI) research and product company that builds models and tools designed to take actions on computers on behalf of users, with an emphasis on enterprise productivity use cases.

• Foundation models and agents for computer-use automation and task execution across software applications (AI agents).
• Enterprise-focused tooling that connects AI agents to existing systems, workflows, and data sources (enterprise automation).
• User interfaces that let employees delegate multi-step workflows to AI while retaining oversight and control (productivity and collaboration software).
• Research and engineering on models that understand natural language, UI elements, and application states to perform actions in real software environments (multimodal AI).
• Infrastructure for secure, controlled deployment of action-taking AI inside organizations (AI infrastructure and orchestration).

More About Adept

Adept focuses on building AI models and agents that operate computers, with a goal of enabling users to delegate complex workflows across standard enterprise applications using natural-language instructions. Its technology is oriented toward action-taking systems rather than only text generation, so the models are trained to interpret user intent, understand user interfaces, and execute multi-step procedures within real software environments.

In enterprise settings, Adept’s offerings are positioned as a layer that sits on top of existing Software-as-a-Service (SaaS) tools, desktop applications, and internal systems. The intended usage pattern is that employees describe outcomes in natural language, and Adept’s agent plans and executes the steps across tools such as Customer Relationship Management (CRM), Emergency Response Plan (ERP), productivity suites, internal dashboards, or web applications, while surfacing intermediate states and results for human review. This aligns the company with categories such as AI agents for business operations, workflow automation, and knowledge-worker productivity.

From a technical perspective, Adept’s work combines large-scale Machine Learning (ML) with interface grounding. Its models are trained not only on text but also on representations of on-screen elements, layouts, and application states, enabling them to Marketing Automation Platform (MAP) natural-language instructions to concrete UI actions such as clicks, form entries, and navigation events. This positions Adept’s stack within multimodal AI and agentic orchestration, where language models are paired with planners, tool-use components, and environment adapters that interact with third-party applications through APIs, browser automation, or other integration mechanisms.

For enterprise adoption, Adept emphasizes deployment patterns that align with security and governance requirements. This includes running action-taking agents within controlled environments, enforcing permission scopes, and integrating with existing identity and access management systems so that the AI operates under defined roles. Logging and observability of actions enable audit trails, which are relevant for regulated industries and for organizations that require traceability of automated changes across systems.

In a marketplace taxonomy, Adept fits into categories such as AI agents for knowledge work, enterprise automation platforms, and AI orchestration infrastructure. Its technology is relevant to teams responsible for digital operations, shared services, and productivity tooling who are evaluating ways to augment human workflows without replacing underlying business applications. By focusing on models that can directly operate existing software, Adept provides an approach that overlays current application stacks rather than requiring wholesale migration to new systems.