BOOMI, LP

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.

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.

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.

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.

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.

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.

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 displaying complex data in three-dimensional graphical formats, allowing users to manipulate, explore, and derive insights from the data through interactive controls.

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.

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

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.