Company patents
Acronis International GmbH
Acronis International GmbH's patent strategy heavily emphasizes Computer Security, which accounts for 53.9% of its portfolio, showing consistent growth in 2024 (+4.8%) and 2025 (+11.4%) before a partial year decline in 2026. Surprisingly, despite its core focus, the company also shows an emerging interest in Network Security & Access Control, which saw a significant 66.7% year-over-year growth in 2025, suggesting a broadening of its security offerings beyond traditional computing.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
271 US filings (since 2023) · 12 categories · 28 themes
Systems and methods for identifying and blocking unauthorized access, malicious activities, or abnormal behavior within a network by analyzing traffic, system logs, or behavioral patterns.
Systems and methods for encrypting data at a fine-grained level (e.g., per data unit or based on sensitivity) and controlling access to it, often involving delegated authorization, contextual policies, or secure data sharing.
Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.
Encompasses strategies and technologies to ensure the availability, integrity, and recoverability of data and systems, including robust backup, replication, error correction, and efficient data restoration.
Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.
Systems and methods for automatically deploying, configuring, and updating network devices and services, including software updates, client onboarding, and topology management across various network types.
Systems and methods for collecting, processing, and ensuring the quality and consistency of data used for network monitoring, asset management, and operational decision-making, including conflict detection and reliability scoring.
Systems and methods for authenticating users, devices, or applications, authorizing their access to resources based on policies, and managing digital identities across various platforms.
Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.
Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.
Systems and methods for securely and reliably delivering, installing, and managing software or firmware updates to distributed or embedded devices, often considering network conditions, resource constraints, or storage repartitioning.
Techniques for monitoring system components and behaviors to anticipate failures, performance degradation, or anomalies, often leveraging machine learning for pattern recognition and forecasting.
Involves systems designed to automatically detect errors or failures and initiate predefined or intelligent corrective actions, recovery procedures, or notifications to minimize downtime and manual intervention.
Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.
Specialized cybersecurity solutions designed to protect industrial control systems (ICS), SCADA networks, and other operational technology environments from cyber threats and unauthorized access.
Systems that use user data, preferences, and machine learning to generate tailored advice, product recommendations, goal-setting plans, or contextual information for individuals across different domains.
Techniques and systems designed to monitor network health, diagnose issues, optimize traffic flow, and ensure continuous operation and reduced downtime in complex network environments, including cloud and storage area networks.
Systems and methods for automating multi-step tasks, business processes, or service interactions, often involving AI agents, programmable interfaces, or formal orchestration languages to streamline operations.
Focuses on using distributed ledger technology (DLT) like blockchain to secure financial transactions, manage digital identities, or ensure data integrity and traceability across various applications.
Methods and apparatus for detecting objects and determining their three-dimensional position and orientation (pose) using imagery or point cloud data, often for navigation, surveying, or environmental understanding.
Platforms and methods for aggregating data from diverse sources, generating dynamic content, and delivering it efficiently to users, often involving social media, programmatic advertising, or interactive experiences within cloud environments.
Technologies enabling the creation and management of virtual computing environments, including virtual machines and virtual desktops, with an emphasis on secure and efficient remote access, updates, and performance.
Methods and apparatus for improving the visual fidelity, resolution, or compression efficiency of video signals, often through advanced processing, up-scaling, or neural network-based filters.
Technologies for deploying, managing, and governing applications and services in cloud environments, particularly focusing on containerization, microservice architectures, API gateways, and distributed data management.
Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.
Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.
Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.
Development and optimization of novel neural network layers or architectures specifically designed to improve performance or efficiency for computer vision tasks.
Patents
Showing 1-10 of 424