USE CASE: COGNITIVE AI
Create GenAI search and recommendation applications that seamlessly combine text and image data.
THE CHALLENGE
Navigating complex GenAI development
Enterprises are looking for cognitive AI solutions that handle diverse data modalities and adapt to future needs with enterprise-grade security, compliance, and scalability. Building these multimodal GenAI applications often requires developers to use unfamiliar tools and undertake resource-intensive, error-prone processes such as data preparation and model selection—resulting in slow GenAI application deployment and subpar customer experiences.
OUR SOLUTION
Multimodal GenAI, simplified
AI Accelerator from EDB Postgres® AI simplifies the development of multimodal GenAI applications by combining built-in vector data and search capabilities from pgvector with the Pipelines extension, which enables automated creation, updates, and retrieval of text and image vector embeddings—all within reliable, familiar Postgres.
Enterprise-ready vector toolkit
The Pipelines extension comes preloaded with pgvector for seamless management of vector data in Postgres, enabling developers to build complex GenAI functionality using SQL commands in the familiar Postgres environment—with just 5 lines of code instead of 130+—backed by enterprise-grade tools and support.
Automated Pipelines
The Pipelines extension provides automated data fetch from Postgres or object storage, generation of vector embeddings as new data is ingested, and triggered updates to embeddings when source data changes—streamlining the creation of multimodal AI search and analytics applications.
Multimodal support
The Pipelines extension natively supports text and image modalities, providing the flexibility required to handle diverse customer interactions and data sources.
DEMO VIDEO
DEMO VIDEO
Bring AI Models to Your Postgres Data
Bring AI Models to Your Postgres Data
Significantly improve customer support efficiency, cost optimization, and market competitiveness through seamless data integration and high-performance AI capabilities.
Seamless integration of diverse data
Customer support teams can effortlessly manage and operationalize diverse data types with a single, familiar platform. This eliminates the need for complicated, high-latency multi-platform solutions.
High-performance search
The pgvector extension powers 4.22x faster queries, on average, than specialized vector databases, enabling responsive and accurate semantic search across all customer data types.
Faster time-to-market
With automated data retrieval, embedding generation, and storage, teams can focus on solving business problems, leading to faster implementation of AI-powered applications.
Looking for end-to-end GenAI?
We're partnering with Griptape to provide everything you need to build, deploy, and manage enterprise GenAI applications—with 100% data control and the familiar Postgres experience your admins love.
EDB Postgres AI enables cognitive AI
AI Accelerator leverages the Pipelines extension’s Intelligent Retriever to fetch data from Postgres or object storage, and then Auto Embedding seamlessly converts data to vector embeddings using chosen models—which are kept up-to-date with source data via triggers. The Intelligent Retriever fetches generated embeddings and prepares them for semantic search against text or image user inputs, which are converted to embeddings using the same GenAI encoder.
Related Products and Solutions
EDB Postgres AI
A modern Postgres data platform for powering mission-critical workloads from edge to core.
EDB AI Accelerator
The fastest way to test and launch enterprise GenAI applications, with the powerful EDB Pipelines extension that comes preloaded with pgvector.
Sovereign AI Use Case
Your controlled, adaptable AI platform—secure, flexible, and cost-effective where your data lives.
Virtual Expert Use Case
Build custom chatbots, copilots, translators, and more with automated GenAI data orchestration in enterprise-hardened Postgres.
Resources
More Personalized Service, Less Waiting: How AI is Transforming Insurance Contact Centers
Unleashing AI with Torsten Steinbach
What Is pgvector, and How Can It Help You?
Enhancing Search Capabilities with PostgreSQL: From Standard to Semantic
Cognitive AI refers to intelligent systems capable of search, analysis, and recommendation across diverse data modalities, including text and images.
Cognitive AI addresses challenges such as:
EDB provides the AI Accelerator solution that simplifies multimodal data management, enabling faster development of multimodal AI search and analytics applications while maintaining enterprise-grade security, compliance, and scalability.
Key features include:
- Built-in pgvector for seamless vector management in Postgres
- Automatic fetch, creation, updating, and storage of vector embeddings with the Pipelines extension
- Seamless handling of text and image data modalities
The Pipelines extension natively supports text and image data modalities, providing flexibility to handle diverse customer interactions and data sources.
Benefits include:
- Seamless integration of diverse data types
- High-performance search (4.22x faster queries on average)
- Automatic AI data management
- Cost optimization
- Improved customer experience
- Faster time-to-market for AI-powered applications
EDB's advanced query engine powers 4.22x faster queries, on average, than specialized vector databases, enabling responsive and accurate semantic search.
Yes, AI Accelerator leverages the Pipelines extension to automatically fetch, create, and store vector embeddings in Postgres, streamlining the creation of multimodal AI search and analytics applications.
Yes, EDB's solution is designed for enterprise use, offering enterprise-grade security, compliance, and scalability to handle growing data volumes and evolving AI technologies.
By automating key processes and streamlining the integration of diverse data types, AI Accelerator helps bring AI-powered applications to market more quickly, reducing development bottlenecks.
While beneficial for many industries, this solution is especially valuable in sectors such as healthcare, finance, and retail, where data integrity, regulatory compliance, and customer experience are paramount.
By consolidating data management and processing in Postgres and leveraging AI to extract more value from diverse data types, organizations can reduce infrastructure and personnel costs while improving scalability.