US20260032155
2026-01-29
Electricity
H04L63/20
The patent application details a system that integrates generative artificial intelligence (AI) within Software-as-a-Service (SaaS) platforms. This integration is designed to automate data operations, synchronize workflows across platforms, and enable intent-based interactions. The system uses table structures to organize items and characteristics linked to common objectives, and incorporates AI agents as credentialed users who can read and write data. These agents are guided by prompts that include column types, structural relations, and role profiles to generate and execute instructions that aid in workflow progress, data consistency, and user notifications.
AI agents in this system act as autonomous team members with hierarchical access schemes, allowing multiple instances with inherited privileges and resource limits. These agents can analyze outputs, support natural-language explanation sessions, and detect deviations or inconsistencies in data. The system's AI center manages these agents, ensuring efficient deployment and resource management. This setup enhances automation, decision support, and operational efficiency within complex SaaS environments.
The system facilitates intent-based interactions by maintaining AI agents configured to interact with alphanumeric data in table structures. Agents are assigned roles with specific rules guiding their data interactions, which can be adjusted as needed. A credentials management process controls user access, and the system allows agents to interact with data under this process's supervision. This setup ensures that AI agents can perform tasks effectively while adhering to predefined guidelines.
An interactive analysis system is also part of the invention, allowing AI agents to autonomously perform tasks and generate outputs stored with metadata. Users can initiate natural language sessions to discuss these outputs, receiving explanations based on their queries. Additionally, the system offers contextual data analysis, where AI models assess data structures and perform analyses based on column properties. This capability supports informed decision-making and enhances productivity.
The system includes an AI center interface for managing multiple AI agents and their deployment, ensuring resource limits are not exceeded. The platform's design addresses critical challenges in data management, task automation, and decision support, while maintaining controls for data privacy and security. This integration of AI within SaaS platforms holds the potential to transform business interactions, leading to increased productivity and improved operational efficiency across various industries.