Exploring Agentic AI and Intelligent Automation
Welcome to Memra, where we advance Agentic AI and intelligent automation. Explore our videos to see how our AI agents handle complex tasks beyond basic information retrieval. Learn about real applications, including document-to-database functions and workflow automation. We demonstrate how agents extract data from legal documents, write to databases, and manage data accurately using data models, metadata, and knowledge graphs.
Document-to-Database Capabilities with Agentic AI
In this video, we introduce Memra agents powered by language models, designed to perform tasks while maintaining context. Unlike traditional tools, these agents don’t just retrieve information—they perform job functions. Watch as I demonstrate how an agent extracts data from a legal document and writes it to a database, showcasing the potential of these agents to streamline and automate complex tasks.
AI Agents in Action—Task Delegation and Workflow Automation
In this video, we demonstrate the capabilities of Memra’s AI agent in extracting data from a document and accurately writing it to a target database. The video covers the importance of data models and metadata in ensuring precise data handling and provides a real-world example of how our agent automates complex data processing tasks.
AI Agents in Action—Task Delegation and Workflow Automation
In this video, we demonstrate the capabilities of Memra’s AI agent in extracting data from a document and accurately writing it to a target database. The video covers the importance of data models and metadata in ensuring precise data handling and provides a real-world example of how our agent automates complex data processing tasks.
Ensuring Consistent Data Formatting with Agentic AI
In this video, we demonstrate how Memra’s AI agents extract and write data from documents to databases with consistent formatting. By using a data model and a manifest file, our agents ensure that the correct data is written accurately and uniformly, solving the issue of inconsistent formats. This ensures precision beyond standard contextual retrieval, providing reliable, consistent results.