Company patents
Stripe, Inc.
Stripe, Inc. exhibits a clear focus on its core "Business Methods & Fintech" with 56.5% of its portfolio, but surprisingly, its patenting in this area saw a significant decline of -84.0% so far in 2026. Concurrently, the company has shown an emerging focus on "Machine Learning & AI," with a robust +40.0% YoY growth in 2025, and "Databases & Information Retrieval," which grew by +38.1% in 2025, indicating a strategic shift towards underlying computational infrastructure and intelligence to support its fintech offerings.
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.
462 US filings (since 2023) · 12 categories · 31 themes
Systems designed to streamline and automate various commercial transactions, including mobile-enhanced processes, secure online checkouts, customer service interactions, and privilege issuance, often leveraging digital authentication.
Systems and methods for authenticating users, devices, or applications, authorizing their access to resources based on policies, and managing digital identities across various platforms.
Techniques for distributing computational tasks, data storage, and service logic across cloud data centers, edge devices, and user equipment to improve performance, resilience, or resource utilization. This includes architectures for split rendering, decentralized ledgers, and microservices.
Systems and methods designed to ensure adherence to regulatory rules, corporate policies, or contractual agreements, often involving automated validation of electronic transactions, smart contract enforcement, or API governance.
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.
Designing user interfaces and interaction methods specifically for mobile or wearable devices, enabling control of external systems, monitoring user states, or facilitating real-world transactions.
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.
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.
User interface designs and systems that enable multiple users to interact with shared content, provide feedback, or coordinate activities, often across different devices or locations.
Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.
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.
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.
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.
Techniques for monitoring system components and behaviors to anticipate failures, performance degradation, or anomalies, often leveraging machine learning for pattern recognition and forecasting.
Technologies for securing, managing, and transacting with virtual currencies, non-fungible tokens (NFTs), and other blockchain-based digital assets, including hardware wallets and tokenization schemes for various purposes.
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.
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.
Methods and frameworks for systematically verifying the correctness, performance, and security of software systems, including infrastructure as code, virtual workloads, APIs, and identifying potential vulnerabilities or inconsistencies.
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 identifying and blocking unauthorized access, malicious activities, or abnormal behavior within a network by analyzing traffic, system logs, or behavioral patterns.
Mobile applications and systems leveraging wireless communication and location data (e.g., GPS, RFID, geo-fencing) to provide context-specific services, transactions, or user interactions.
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.
Techniques and tools for automatically identifying, resolving, building, and packaging software dependencies, including managing versions, branches, and ensuring the integrity and security of the dependency chain.
Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.
Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.
Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.
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.
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.
Techniques employed within compilers or related tools to analyze program code, identify entities for compilation, and optimize execution on target hardware, including reconfigurable systems, to improve performance or resource efficiency.
Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.
Focuses on establishing and enforcing quality standards for software development, deployment, and infrastructure configuration, utilizing automated validation, testing, and governance frameworks.
Patents
Showing 41-44 of 44
Granular Data Encryption & Access Control