LLMs and AI Agents: Transforming Unstructured Data
Terzo AI’s metadata extraction transforms contracts, invoices, and financial documents into actionable intelligence, serving as a critical enabler of APA.
Are AI agents the new assembly line for data?
Join Eric Pritchett from IBM partner Terzo as he explores how LLMs, GPT models, and AI agents turn unstructured data into actionable insights.
Discover how OCR, NLP, and agentic workflows reshape document intelligence and solve real-world challenges.
Role of Terzo AI’s Metadata Extraction in Agentic Process Automation (APA)
Agentic Process Automation applies self-intelligent agent design to business workflow, so that individual decision points can act autonomously to improve the performance of the overall process.
To make this possible key technology capabilities are required, such as the ability to access and interrogate legacy documents and data, such as contracts and invoices.
Terzo AI’s metadata extraction is a cornerstone of APA, enabling intelligent, autonomous process reengineering. By providing accurate, structured data, Terzo empowers AI agents to orchestrate complex workflows, make data-driven decisions, and optimize end-to-end processes.
Enabling End-to-End Process Orchestration APA relies on comprehensive, real-time data to reengineer processes. Terzo’s metadata extraction provides AI agents with structured data from contracts and invoices, enabling them to manage entire workflows, such as source-to-pay or order-to-cash, without human intervention.
Terzo AI’s metadata extraction transforms contracts, invoices, and financial documents into actionable intelligence, serving as a critical enabler of APA. By delivering accurate, structured data at scale, Terzo empowers AI agents to reengineer processes, make autonomous decisions, and drive dramatic improvements in efficiency, compliance, and customer value.
