EDB and Red Hat: A powerful combination for the AI-driven enterprise

As artificial intelligence (AI) becomes more ubiquitous, AI innovation and IT modernization are becoming a greater priority for many organizations. And it's in this context that EDB and Red Hat have joined forces to help organizations looking to establish a competitive AI edge.

Powering intelligent applications with EDB Postgres AI, pgvector and Red Hat OpenShift AI

EDB Postgres AI, built on a foundation of PostgreSQL, offers advanced capabilities in security, compliance and high availability. It includes the pgvector extension with an enhanced AI data pipeline, providing a unified solution for storing and querying vector embeddings directly within the database. This reduces the complexity of managing separate vector databases, streamlining the development of AI-powered applications that rely on semantic search and retrieval-augmented generation (RAG).

Red Hat OpenShift AI, part of the Red Hat AI portfolio, provides a comprehensive platform for managing both generative AI (gen AI) and predictive AI lifecycles across hybrid cloud environments. This includes machine learning operations (MLOps) and large language model operations (LLMOps) capabilities, along with tools and integrations that further help accelerate the development and deployment of models and AI-enabled applications.

Leveraging knowledge bases for enhanced AI accuracy

The integration of EDB Postgres AI—featuring pgvector—within OpenShift AI enables the creation and use of knowledge bases. This involves transforming domain-specific information, like text, into vector embeddings—numerical representations that capture the meaning of the data. By storing this information as embeddings in EDB Postgres AI, organizations can employ RAG to enrich the knowledge of LLMs. 

This allows AI applications to deliver more accurate and contextually relevant answers by grounding their responses in internal data. OpenShift AI provides the platform to orchestrate data ingestion, embedding generation (the process of creating these meaning-rich numerical representations), and the subsequent querying.

Exploring agentic AI frameworks on OpenShift AI

Agentic AI frameworks give AI systems the ability to perform complex tasks with a degree of autonomy by breaking those tasks down into smaller steps, using a variety of tools and learning from their interactions. OpenShift AI provides an ideal environment for experimenting with and deploying agentic AI solutions—its flexible architecture supports the diverse components often required by these frameworks, including as LLMs, external tools and orchestration layers.

The ability to store and retrieve relevant information efficiently can be crucial to an agentic AI system. For example, an agent tasked with answering customer inquiries could leverage a knowledge base stored in EDB Postgres AI to quickly retrieve relevant information and formulate comprehensive responses.

Key benefits of the integrated approach

The combined integration of OpenShift AI and EDB Postgres AI provides a variety of benefits, including:

• Simplified AI development: EDB Postgres AI combined with OpenShift AI provides a unified data layer for both structured data and vector embeddings
• Improved accuracy and reliability: Knowledge bases built with EDB Postgres AI help improve the accuracy and reliability of AI applications through RAG
• Future-proofing with agentic AI: OpenShift AI provides a flexible and scalable platform for exploring and deploying advanced agentic AI frameworks
• Modernized data infrastructure: Transitioning to EDB Postgres AI on OpenShift AI provides a modern, open source foundation for many data needs, including complex AI workloads
• Consistent hybrid cloud experience: OpenShift AI provides a consistent experience for developing and deploying AI applications across on-premises, cloud and edge environments

Real-world impact

The combination of EDB Postgres AI and OpenShift AI can be used to build a wide range of intelligent applications, including, but not limited to:

• Enhanced customer service chatbots: Providing more accurate and context-aware support using knowledge bases
• Intelligent document processing: Automating information extraction and analysis from large volumes of documents
• Personalized recommendation systems: Delivering more relevant recommendations based on semantic understanding of user preferences
• Autonomous agents for task automation: Building AI agents that can independently complete complex tasks

The future of intelligent applications is open and integrated

EDB and Red Hat are committed to helping organizations build the next generation of intelligent applications. By tightly integrating EDB Postgres AI into OpenShift AI, EDB is providing a powerful, flexible and future-proof solution for the AI-driven enterprise and helping accelerate their AI innovation journey.