A single GenAI inferencing and agentic platform that breaks free from the complexity trap and transforms your AI initiatives from concept to production in weeks, not months or years.
This blog was co-authored by Jack Christie and Dave Stone.
The pressure to deliver GenAI value has never been higher, but most organizations find themselves caught in a frustrating paradox. While the demand for AI applications accelerates, the complexity of building them continues to grow. What should take weeks stretches into months, what should empower teams creates bottlenecks, and what should drive innovation gets buried under integration challenges. EDB Postgres AI Factory changes the process of building GenAI applications from the foundation up. Our unified GenAI inferencing and agentic platform eliminates the complexity that's been holding your AI initiatives back, enabling you to deploy production-ready applications in weeks instead of months while maintaining complete data sovereignty and governance.
The GenAI integration complexity trap slows time to value
Every organization faces the same challenge when pursuing GenAI initiatives. The rush to deliver results drives teams to piece together off-the-shelf AI components from multiple vendors, creating a fragmented landscape that's both technically complex and operationally risky. This approach creates immediate problems as data gets scattered across numerous external vendors, creating silos that undermine governance and expose sensitive information to security risks. Your scarce AI developer talent spends 50-80% of their time on integration work rather than building innovative solutions, while project timelines stretch from weeks to 6-12 months, leaving business users waiting for AI value that may never materialize.
The result? Many companies abandon GenAI projects before they reach production, despite significant investments. At EDB, our own Data, AI, and Analytics team experienced this firsthand — they needed to dramatically accelerate GenAI adoption across the organization, but traditional approaches were proving too slow and resource-intensive. What should have taken weeks was stretching into months, and what should have empowered teams was creating bottlenecks.
Organizations typically choose between two problematic paths. Some attempt to build everything in-house that add 40 plus new services, creating custom integrations between vector databases, embedding pipelines, model serving infrastructure, and agent orchestration systems. Others rely entirely on external vendors, sacrificing control and governance for perceived simplicity. Both approaches lead to the same outcome: delayed time-to-value and mounting frustration. According to our recent Total Cost of Ownership study by McKnight Consulting Group, organizations using DIY cloud approaches for GenAI deployments face 67% higher development complexity and 38% higher maintenance complexity compared to integrated platform solutions.
From concept to production in weeks with EDB Postgres AI Factory
EDB Postgres AI Factory eliminates the integration complexity that's been slowing your AI initiatives. By combining vector databases, embedding pipelines, model inferencing, observability, and agent orchestration into a single, cohesive platform we enable organizations to deploy production-ready GenAI applications in weeks instead of months or years.
Take a look at this demo to see the power of EDB Postgres AI Factory — and read this how-to guide to recreate it for yourself.
Our comprehensive inferencing and agentic approach addresses three critical business needs simultaneously. Simplified architecture provides a single GenAI inferencing solution that reins in data sprawl and reduces implementation cycles from months to weeks, allowing your teams to focus on business innovation rather than technical plumbing. Universal accessibility ensures both developers and business users can build GenAI applications through flexible low-code and no-code interfaces, eliminating resource bottlenecks. Enhanced data security keeps all data within your trusted Postgres environment rather than sending it to external vendors, enabling complete data sovereignty and governance. This isn't just about faster development — it's about transforming how your organization approaches AI innovation.
Key Features: A complete GenAI inferencing platform built on Postgres
AI Factory delivers five integrated components that work seamlessly together within your existing Postgres environment, providing comprehensive inferencing capabilities for all your GenAI needs.
GenAI Builder empowers every department to build custom GenAI solutions with a robust low-code SDK for developers and an intuitive point-and-click interface for business users. You can ensure security and accuracy with custom Knowledge Bases, rules, and sovereign deployment that protects sensitive data while accelerating development by 3x compared to DIY approaches.
Agent Studio enhances productivity and decision-making with AI agents that perform tasks and take action autonomously. Start with open source agent templates for common use cases or build custom agent workflows tailored to your specific business needs. These intelligent systems unlock new insights and efficiencies by solving problems, performing repetitive tasks, and analyzing vast quantities of data.
AI Pipeline accelerates GenAI time-to-value with set-and-forget AI Knowledge Base for data management. Use just five lines of code to set up an AI Pipeline that automatically syncs embeddings with source data, ensuring always-up-to-date AI Knowledge Bases without costly infrastructure maintenance.
Vector Engine brings together AI and business data in a single, secure location in Postgres, eliminating data movement to external vendors. Gain complete data sovereignty with rapid semantic search powered by open source pgvector and an intelligent retriever that handles vector similarity calculations automatically.
Model Serving provides flexible inferencing capabilities with on-premises model deployment that eliminates vendor lock-in. Seamlessly swap between models as business needs evolve without infrastructure changes, while maximizing ROI on hardware like NVIDIA and Supermicro with intelligent scaling that optimizes inferencing resources automatically.
How customers are using AI Factory
Organizations worldwide are recognizing that the future of enterprise AI lies not in fragmented vendor relationships and complex integrations, but in unified platforms that maintain data sovereignty while leveling up AI development capabilities across teams. EDB Postgres AI Factory represents this advancement — a platform that delivers enterprise-grade GenAI capabilities while keeping your data secure, your development processes simple, and your time-to-value measured in weeks rather than months.
App Modernization with Agents transforms how organizations handle end-of-life software without costly replacements. Instead of rip-and-replace migrations, AI agents act as intelligent middleware between legacy systems and modern interfaces. Users interact through familiar tools like Slack while agents handle the complex interactions with outdated systems behind the scenes. This approach eliminates the knowledge gap and user experience frustrations of legacy software while avoiding resource constraints and business risks of major system overhauls. Organizations can extend the life of critical applications while providing zero code changes and familiar interfaces that continue to add business value.
Agentic Analytics changes how teams interact with data by combining AI Factory and Analytics Accelerator capabilities with intelligent agents that analyze and take action in real-time. Unlike traditional approaches that require manual queries, static dashboards, and human-dependent decision making, agentic analytics pulls together data from different locations — including Iceberg and Delta tables through our Lakehouse Connector — and enables autonomous monitoring with 24x7 intelligent responses. The result is faster lead discovery, reduced manual effort, and higher conversion rates as agents continuously optimize based on real-time insights across your entire data ecosystem.
Dive deeper into agentic analytics and how EDB Postgres AI makes it possible.
Unified Query Engine addresses the complexity of managing multiple query engines across AI, analytics, and transactional workloads. Rather than maintaining separate systems with governance challenges and legacy silos, AI Factory transforms Postgres into a trusted, sovereign engine for search across Postgres, the lakehouse, and anywhere else your data lives. This provides one platform for querying all data with real-time processing capabilities, while improving efficiency, flexibility, scalability, and security. Organizations eliminate the fragmentation of too many specialized systems while gaining the performance benefits of 30x faster queries compared to standard Postgres, and agents to take action.
Proven results: Customer success and measurable ROI
Our own transformation with AI Factory here at EDB demonstrates both the platform's potential and its measurable business impact. A few of our internal AI teams have been working on a GenAI project for an entire year using traditional approaches, while our Data, AI, and Analytics team implemented a custom GenAI application in just hours using AI Factory — without tapping any engineering resources. The dramatic difference in development velocity prompted engineering to pivot and leverage AI Factory, completing a production-ready rebuild in weeks instead of continuing their year-long effort.
"EDB Postgres AI Factory took off like wildfire within EDB. What used to take us a year, we now deliver in weeks. It's fundamentally transformed how we bring GenAI to life — faster, more securely, and at scale."
— Dan Merzlyak, SVP, Global Head of Data, Analytics, and AI at EDB.
This transformation enabled EDB to turn their data, IT, and infrastructure teams into GenAI developers, enabling faster POCs and applications and achieving 3x faster time to market compared to DIY approaches.
The business case extends beyond development speed. Our comprehensive Total Cost of Ownership analysis, conducted by McKnight Consulting Group, evaluated the full costs of building and maintaining RAG-based AI applications, including infrastructure, licensing, development effort, and ongoing operational requirements. The results show that EDB Postgres AI Factory reduces total cost of ownership by 51% over three years compared to DIY cloud solutions, while providing 67% lower development complexity and 38% lower maintenance complexity.
These savings come from multiple sources: smaller teams requiring less specialized AI expertise, operational costs decrease through simplified architecture and reduced vendor management overhead, and infrastructure costs become more predictable with on-premises deployment. Most importantly, the platform enables organizations to confidently leverage sensitive data for AI applications without the security and compliance risks associated with sending data to multiple external vendors.
The future of AI is sovereign, secure, and accessible
Whether you're looking to enhance existing Postgres environments with AI capabilities, migrate from costly and restrictive cloud-based solutions, or launch your organization's first GenAI initiatives, AI Factory provides the foundation for sustainable AI innovation that scales with your business needs. Ready to transform your GenAI initiatives from concept to production in weeks? Discover how EDB Postgres AI Factory can eliminate the complexity that's been holding your AI projects back while maintaining the security and governance your organization requires. Contact our team to explore how AI Factory can accelerate your path to AI-driven business value, or request a demo to see the platform's capabilities in action to get your use cases going.
For a comprehensive look at all the latest advancements on EDB Postgres AI, be sure to read our main Q2 release blog.