AI Agents

Content Intelligence extracts, chunks, and enriches diverse data formats and modalities, making information easily accessible to AI Agent frameworks.

The problem

AI Agent-based automation solutions frequently encounter the need to access and manipulate enterprise knowledge stored in various repositories and formats. However, this knowledge often lacks proper structure and necessary metadata to support AI automation. Engineering teams are compelled to undergo a slow process of data preparation, often necessitating feedback from business stakeholders. This sluggish pace of progress results in teams not moving fast enough, and AI automation solutions failing due to inadequate data structures.

The solution

Content Intelligence handles data integration and enrichment and makes enterprise knowledge easily accessible and properly structured for AI Agent frameworks.

[ Steps to solution ]

Content Intelligence simplifies data integration and transformation through its 15 pre-built connectors and format specific content processing. This makes enterprise knowledge easily accessible and readily available to AI Agent solutions.

Content Intelligence automatically enriches processed data through techniques such as topic modeling, categorization and tagging, metadata extraction, and textual image and table representation. By evaluating content quality and flagging potential risks like conflicting or outdated information, Content Intelligence ensures data reliability. Using extracted and generated metadata, engineering teams can implement advanced AI automation pipelines such as user specific content retrieval and information-augmented LLM generation.

Content Intelligence adopts an API-first approach and provides thorough developer documentation and SDKs for Python and Javascript, facilitating integration with any LLM or AI Agent framework. Developers can also opt to use the hybrid information retrieval built in Content Intelligence and focus on creating custom AI Automation chains.