The adoption of Artificial Intelligence (AI) technology into all aspects of our lives has been staggering. It took ChatGPT only two months to reach 100 million users. In contrast, Instagram took 30 months to reach 100 million users.

In the enterprise world, the integration of AI Retrieval-Augmented Generation (RAG) strategies is raising the bar even further. RAG, put simply, is AI working with YOUR documents and data to produce results specific to your use case, company or industry. 

To dive deeper into what AI RAG is, view our previous blog, What is Retrieval-Augmented Generation.

Veladocs stands out as the ideal platform to support and enhance AI RAG strategies. This blog will share why Veladocs is the perfect solution for effectively implementing content-based AI RAG strategies within your organization.

Why Veladocs for AI RAG?

1. Seamless Integration – Veladocs enables direct access to content and data through AWS or Azure APIs, integrations that are out-of-the-box offerings from any major AI vendor.  Legacy ECM solutions require access funneled through proprietary API and database layers, layers of technology that would require custom development and integration with an AI vendor.

2. Support for Security and Compliance – Security and compliance are non-negotiable in content management, particularly when handling sensitive information. Veladocs’ AI RAG approach offers strong security features, ensuring that only authorized users can access sensitive data and that only the correct data enters the AI engine. This approach includes encryption and access controls, ensuring that information remains secure against unauthorized access and compliant with industry regulations.

3. Dynamic Content Handling – Veladocs supports changing or versioned content. While many AI RAG strategies allow for new content to be added, most do not support forgetting content that is out to date, allowing it to be replaced with new up-to-date information. Veladocs supports content versioning, content replacement, and full removal of content. For example, suppose a patient undergoes a significant treatment change or a correction is made to a previously documented diagnosis. In that case, the old versions of the record need to be carefully managed. It is crucial that the most current and accurate information for ongoing care is accessed while ensuring that outdated or incorrect information is no longer referenced. 

4. Traceability – Veladocs supports the attribution of source documents. For example, if an employee is looking for instructions on how to replace a valve on a pump, the instructions, mechanical drawings, and other relevant information can be included in the response.  This enhances end-user trust since the AI engine provides links to source material used to generate the responses.  Additionally, attribution offers valuable information for IT, allowing them to understand how the AI engine works and providing data points to target further training and tuning. Source attribution is supported because of Veladocs real-time RAG approach. To learn more about what real-time RAG is and how it differs from other approaches, view this blog.

5. Enhanced Retrieval – RAG implementations involve a “smart retriever” intercepting the question/prompt sent to the AI engine and supplementing that prompt with additional relevant content. What content is added and how it is retrieved is critical in ensuring that the responses are truthful and highly relevant. Veladocs’ ability to find related content based on full text and/or attribute searching offers a significant advantage. Google and fuzzy searching are great for personal use but are not always precise enough for business use. For example, when analyzing contracts greater than one million dollars for ACME, one wouldn’t want to include similar contracts from other vendors.  A similarity search will always return information to the end-user when, in fact, the answer may be that no contracts greater than one million dollars for ACME Corp exist. Attribute-based searching is imperative to minimize hallucinations. 

6. Targeted Information – Veladocs supports segregating content into multiple search indices. This allows the AI RAG engine to focus on content relevant to the end user’s domain of interest—traditional, legacy applications, in contrast store all content in a single index.  Segregating content into separate indexes allows for efficient searching against targeted data sets. For example, users in the R&D department executing a search would want to target R&D content, not financial or logistics content and information. 

7. Separation & Control – Veladocs caches content that is accessed by AI engines preventing AI processes from directly accessing the main content repositories. Once the documents are ready for use in AI searching (i.e., content becomes approved or released), they will be published to Veladocs. An ongoing synchronization job runs every few minutes removing stale content and adding new content, ensuring that Veladocs always has the most up-to-date information.  This allows content to be made available for AI searching while also providing a logical separation between the working ECM repository and the AI processes. 

8. Enterprise Scalability – Veladocs can easily scale to support billions of content and data files. As AI use cases grow, the need for AI engines to access internal content and data will quickly soar into the billions of objects. A cloud-first repository, such as Veladocs, is suited to handle this volume. In contrast, traditional server and database systems have struggled when asked to manage content at this volume.  The Veladocs architecture is 100% cloud services, which can scale individual services up or down as required.  For example, compute services can be scaled up when receiving a high content volume or performing analysis across large content sets. The compute services can be scaled down once the ingestion or analysis is complete.  

The Future is Here

Veladocs is more than just a content management system—it’s a comprehensive platform that empowers organizations to implement AI RAG strategies with precision and efficiency. By integrating Veladocs into your AI-driven content processes, you’ll benefit from advanced content management, transparent access to content, and the benefits of working in a modern cloud services platform, all of which are crucial for the successful execution of AI RAG strategies.

In a world where content is king, Veladocs provides the tools and capabilities needed to stay ahead of the content curve. Whether you’re looking to improve accuracy, boost efficiency, or simply use your content better, Veladocs is the partner you need for your AI RAG journey. Contact us to learn more about how Veladocs can fit into your AI roadmap.