Infosys Limited

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 utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.

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.

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 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 systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.

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 for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.

Methods and systems for monitoring, controlling, and managing Internet of Things (IoT) devices and their communication networks, often involving adaptive or intelligent frameworks for data acquisition, relay, and automation.

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.

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.

AI systems designed to engage in natural language dialogue, maintain conversation state, understand user intent, and generate relevant responses, often across multiple communication channels or modalities.

Methods and systems for improving the quality of video streams, generating intermediate frames, or continuously locating and following objects within a sequence of images, even under occlusion.

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.

Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.

Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.

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.

Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.

Automated systems using image processing and artificial intelligence to identify, classify, and assess the extent of damage to structures or objects, supporting maintenance or insurance claims.

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.

Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.

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 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.