RavenDB, a trusted multi-model NoSQL document database used by developers and enterprises worldwide, has unveiled its AI Agent Creator, a groundbreaking feature fully integrated into the database that drastically reduces AI agent development timelines. What previously took weeks, months, or even years can now be achieved in just days.
Gartner highlights AI agents as one of the fastest-growing technologies on its 2025 Hype Cycle. However, a recent MIT study revealed that 95% of enterprise AI projects fail to deliver measurable business impact. The reason is not the AI models themselves but the complexity of embedding them into existing workflows and data systems. By running agents natively inside the database, RavenDB’s AI Agent Creator removes this barrier. It provides developers secure, direct access to operational data while automating integration, transforming months of uncertainty into days of reliable, context-aware AI delivery.
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“Consumers can already plan meals, design entire trips, or get advice from AI platforms such as ChatGPT and Gemini in seconds, yet enterprises are still stuck with rigid, scripted chatbots,” said Oren Eini, CEO and Founder of RavenDB. “Our AI Agent Creator is the missing piece, enabling developers to build fully integrated agents directly within the database, with secure access to live operational data so that they can go from idea to proof of concept in minutes, and production-ready agents in a matter of just a few days.”
Unlike traditional scripted bots or AI-assisted chatbots limited to generic knowledge, RavenDB’s solution allows developers to deploy intelligent agents with built-in guardrails. Developers set the boundaries for each agent’s operations and effortlessly integrate them with existing validation, authorization, and business processes. To enhance control, safety, and precision, the large language model (LLM) follows a zero-trust, default-deny approach, meaning no data or operations are accessible unless explicitly approved.
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When an end-user submits a request in natural language, RavenDB invokes the agent to process it, orchestrating the entire flow by referencing existing business logic. This ensures accurate, personalized responses without exposing the full database, transferring data externally, or writing complex integration code while maintaining enterprise-grade security.
The AI Agent Creator supports all LLMs and leverages smart caching, summarizing agent memory and history to reduce redundant requests for reasoning-intensive tasks. This optimization cuts AI costs significantly without compromising accuracy, making it a powerful efficiency tool for agentic AI workflows.
Now available in RavenDB 7.1, the AI Agent Creator enables customers to start building and deploying AI agents immediately across cloud, on-premises, and edge environments without re-architecting systems or compromising data security.
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