RavenDB Launches the First Fully Integrated, Database-Native AI Agent Creator

Unlike the limited embedded solutions on the market, this first-of-its-kind feature lets developers build fully native AI agents to turn existing data into personalized experiences.

HADERA, Israel, Sept. 8, 2025 /PRNewswire/ -- RavenDB, a multi-model NoSQL document database trusted by developers and enterprises worldwide, today announced the launch of its AI Agent Creator, a first-to-market feature fully integrated into the database, that reduces the time required to build AI agents from weeks, months, or even years to just days.

Gartner recently named AI agents one of the fastest-rising technologies on its 2025 Hype Cycle, yet a recent MIT study found that 95% of enterprise AI projects fail to deliver business impact, not because the models fall short, but because embedding them into workflows and data systems is too complex. RavenDB's AI Agent Creator removes that barrier by running agents natively inside the database, giving developers secure, direct access to operational data. By keeping agents close to the data and automating integration, RavenDB turns months of uncertainty into days of reliable, context-aware AI delivery.

"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 scripted bots or AI-assisted chatbots limited to generic knowledge, with the AI Agent Creator, developers can deploy intelligent agents with built-in guardrails. Developers define the scope in which each agent can operate on behalf of specific users, while seamlessly connecting to existing validation, authorization, and business logic. To give developers stronger control, enhanced safety, and greater precision over how data and operations are accessed, the large language model (LLM) follows a zero trust, default deny approach, where no data or operations are accessible unless explicitly approved.

When an end-user submits a request in natural language, RavenDB invokes the agent to process the request and communicates the tools and actions it has within the scope defined by the developer. RavenDB then orchestrates the entire flow, referencing existing business logic to perform approved operations. This process provides accurate, personalized responses without ever exposing the full database, moving data to external servers, writing complex code, or compromising security.

The feature supports all LLMs and uses smart caching, summarizing agent memory and history, reducing redundant requests for reasoning-intensive tasks. This significantly cuts AI spend and optimizes costs without sacrificing accuracy, making it a critical efficiency tool in agentic AI workflows.

Now available as part of RavenDB 7.1, the AI Agent Creator lets customers start building and deploying agents immediately, without re-architecting systems or compromising data security. RavenDB agentic AI runs across cloud, on-premise, and edge environments.

To start using RavenDB's AI Agent Creator Tool today, visit: https://ravendb.net/lp/ai-agent-creator?utm_source=pr&utm_medium=article&utm_campaign=ai_agents_pr_2025

About RavenDB:

RavenDB is a hybrid NoSQL document database built for modern application development. Used by 12,000 companies across 50 industries, RavenDB helps teams move faster with seamless data management across cloud, on-prem, and edge environments. With full-text search, automatic indexes, and an easy-to-use studio for monitoring and administration, RavenDB is the database developers love and enterprises trust. Learn more at www.ravendb.net. 

Contact
Shahni Ben-Haim
SBH Media Relations
shahni@sbhmedia.com

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