Convergence

Convergence Proxy is a personal AI assistant engineered on Large Meta Learning Models (LMLMs). It evolves with every use, learning from interactions, adapting to the user's work style and preferences, and developing new skills. Proxy's unique features include continuous learning, memory retention and recall, individual workflow personalization, and independent task execution.

Proxy adapts to a user's work style and preferences through continuous interaction. It learns from each interaction, thereby adapting to varying workflows and individual tasks. Over time, Proxy refines its understanding of a user's preferences, becoming an extension of them and their work.

The specifics of the unique skills Proxy acquires through interactions are not explicitly stated on their website. However, it is mentioned that Proxy is capable of remembering and learning from every interaction, continually adapting and remembering tasks to improve efficiency and intelligence. This suggests that the skills acquired would be specific to the user's individual workflow and preferences.

Proxy’s continuous learning and remembering feature enables it to remember past tasks and interactions, which in turn allows Proxy to operate more efficiently and intelligently. This feature promotes a refined and personalized user experience, increasing productivity by minimizing redundancy and proactively fulfilling tasks based on learned knowledge.

Proxy is designed to adapt to the unique workflows and preferences of its users. It learns individual tasks and how various actions are accomplished, then tailors its functionality to those specific requirements, effectively making it a user-specific study and assistance tool. This personalization allows for a more intuitive and effective workflow management process.

Yes, Proxy can seamlessly integrate with other systems in an enterprise setting. Its enterprise-ready design ensures it delivers secure, compliant, and scalable solutions that can be integrated with multiple systems, empowering the entire organisation.

The Large Meta Learning Models (LMLMs) powering Proxy allow it to handle complex tasks with extreme efficiency. With LMLMs, Proxy is designed to continuously learn and gain new skills, similar to a human. This design assists Proxy in handling various complex tasks, from remembering interactions and recalling past interactions, to automating tasks and facilitating workflow management.

Proxy enhances operational efficiency by autonomously executing tasks and managing processes, eliminating the need for constant user oversight. It learns workflows and preferences, allowing it to autonomously execute tasks and save users' time. Proxy's ability to automate tasks and manage processes independently drastically reduces repetitive task execution, giving users more time to focus on important aspects.

Proxy learns tasks based on user action, allowing it to automate them. The tasks that Proxy can automate range from daily routines to more complex work tasks. Its automation capabilities extend to various tasks such as updating Shopify sites with new product prices, organising meetings, booking deliveries or flights, posting job adverts, sending emails, forecasting sales in Salesforce, and more.

Proxy's memory retention and recalling feature works by storing details of past interactions and leveraging this accumulated knowledge to improve the assistance provided over time. This feature allows Proxy to perform tasks more precisely and intelligently, based on remembering past interactions, preferences, and workflows of the user.