The Harsh Reality: Why Most Enterprise AI Projects Fail
In today's fast-paced world, Artificial Intelligence promises to revolutionize every industry. Yet, the truth is stark: a staggering 95% of enterprise AI projects fail to deliver value[^1]. Why? They are often context-less, unable to access the rich, real-time data needed to make intelligent decisions. This happens because the complexity of integrating AI models with existing data, the security challenges of moving sensitive information, and the sheer development time required often create insurmountable hurdles. Developers are left grappling with fragmented systems, data silos, and a constant battle to secure their AI workflows, resulting in solutions that are disconnected from the value and experience users expect today.
But what if the solution wasn't another external tool or a complex integration layer, but something far more fundamental – something built directly into the heart of your data?
RavenDB, an industry-leading NoSQL document database, today announces a groundbreaking answer to this challenge with the launch of its AI Agent Creator. This innovative feature is the first fully integrated, database-native AI agent creator, designed to empower developers to build production-ready, context-aware AI agents directly within the database, turning months of development into mere days.
A New Era: AI Agents Built Directly into Your Database
RavenDB's AI Agent Creator fundamentally redefines how AI is built and deployed. Instead of wrestling with external connectors, complex ETL processes, or the security nightmares of sending your entire dataset to an external Large Language Model (LLM), RavenDB brings the AI agent directly to your data.
"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.”
Key Capabilities That Set RavenDB Apart:
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Database-Native Integration
Benefit: Say goodbye to complex API calls and data synchronization issues. AI agents run directly within your RavenDB instance, giving them instant, secure access to live, transactional data without ever leaving the database boundary. This drastically simplifies development and enhances performance.
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Zero-Trust, Default-Deny Security Model
Benefit: Security is paramount. RavenDB's AI Agent Creator provides granular control over what data an AI agent can access and what actions it can perform. You define strict policies, ensuring sensitive information remains protected and LLMs only access what you allow.
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Rapid Development & Deployment
Benefit: Transform your AI project timelines. By eliminating much of the traditional integration work, developers can build, test, and deploy sophisticated, context-aware AI agents in days, not months.
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LLM Agnostic & Future-Proof
Benefit: Whether you prefer OpenAI, Google AI, Ollama, or any other LLM, RavenDB's AI Agent Creator is designed to integrate seamlessly. This flexibility ensures your applications are not locked into a single provider and can evolve with the rapidly changing AI landscape.
Solving Real-World Problems, Securely and Efficiently
By empowering developers to build agents that operate directly on live, transactional data, RavenDB unlocks a new class of intelligent, inherently secure applications.
The following examples illustrate possible use cases where AI agents, integrated with databases, can enhance efficiency, security, and user experience across different industries:
Customer Support: Imagine an agent that instantly provides personalized support by accessing a customer's complete purchase history and open tickets. It can securely retrieve invoices or re-issue them with predefined permissions, drastically reducing resolution times.
E-commerce: A dynamic shopping agent can provide up-to-the-minute information on product availability and offer personalized recommendations based on real-time inventory and purchase history, creating a more engaging shopping experience.
Human Resources: An HR assistant agent can securely access employee records and company policies to answer common inquiries or even initiate leave requests, all while adhering to strict data governance.
Logistics & Manufacturing: An operations agent can transform efficiency by analyzing live sensor data and production schedules to proactively identify bottlenecks, predict maintenance needs, or automate routine tasks.
The RavenDB AI Agent Creator provides the robust, secure, and deeply integrated foundation for these next-generation applications, ensuring your AI projects deliver tangible value by building intelligence directly where your most valuable asset, your data lives.
The Future of Enterprise AI is Here
The RavenDB AI Agent Creator, available now as part of RavenDB 7.1, represents a significant leap forward in enterprise AI. It empowers developers to overcome the most common hurdles to AI adoption by offering unparalleled security, integration, and speed.
Ready to Build Smarter AI?
For a limited time, RavenDB is including the new AI Agent Creator with its free developer license, giving you a unique opportunity to build and test powerful, production-ready AI agents at no cost.
Learn More: Visit the RavenDB AI Agent Creator page for detailed documentation.
RavenDB Features: Visit the RavenDB Features page for a detailed look at what's new, including generative AI integration, Full-Text Search and more.
Top comments (8)
Interesting Article and concept Om!
But how does this RavenDB will ensure that embedding AI agents directly in the database won’t compromise performance And open up new weird security risks?
Thanks Anna, Glad you liked it! Honestly I was worried about that too but RavenDB runs the agents right inside the DB, so no extra API calls slowing things down. And on security, it’s locked down with a default-deny model, so agents only touch what you explicitly allow.
Well-written article, but does building agents directly in the database really speed up development?
Thanks Sir! Glad you liked it.
Instead of sending your sensitive information to an outside AI service, RavenDB lets us build our AI agent directly inside the database. This keeps your data safe and speeds up development by getting rid of complex data setups. Hence making it so Easy!
Quite a well-written article! But how does the AI Agent Creator actually access live data without exposing sensitive information? Do you have any idea about that?
Thanks Sir! Glad you liked it, and regarding how The AI Agent Creator actually access live data without exposing sensitive information is that the AI agent is not a separate entity that pulls data from the database. It is an internal component that is given highly controlled, secure access to the data. Hence ensuring it remains protected at all times.
Interesting...
Thanks ma'am