SWIRL is the AI Infrastructure Software that you need
What is AI Infrastructure Software?
AI infrastructure software is essential for deploying on-premises AI solutions. It performs various functions, such as data mastering and movement, similar to traditional Extract, Transform, and Load (ETL) processes, but AI infrastructure software doesn’t move data but rather facilitates communication between different layers. It operates as a middle layer between data, AI infrastructure, and large language models (LLMs), ensuring that end-users can harness the power of AI without compromising data security or compliance. Additionally, this software facilitates connectivity among various components of AI solutions, including back-end data sources, applications, and interfaces like chatbots. Examples of tools that support such connectivity include SWIRL and LangChain.
Another critical role of AI infrastructure software is compliance and management. It includes tools that help manage and control the various elements of AI systems, ensuring they meet regulatory and policy requirements. A notable example of such a management tool is Bookend.ai, similar to Collibra’s functionality. These tools are integral to maintaining the integrity and security of AI solutions, ensuring they operate within established guidelines.
What Problem Does SWIRL Solve?
The first-generation AI solution architecture was vendor-driven and oriented towards bringing all data necessary to answer questions to the AI installation—the database model if you will.
This is extremely effective when a single corpus of data or a few public corporations—even large ones—are sufficient to meet the needs of the AI solution’s users.
However, when access to many data sources is required, the sources are voluminous, and access is strictly controlled – especially where it is regulated, such as in life sciences, healthcare, and financial services – this architecture is a non-starter.
SWIRL, built by unified search experts, thought about the problem differently and offers a real solution to generate AI insights using internal data WITHOUT having to extract, transform, and load (ETL) all the data.
SWIRL AI Connect’s “real-time” architecture makes different assumptions:
- The “systems of record” are generally kept up to date at a tempo suitable for existing operations
- There is a single sign-on infrastructure that provisions each user access to data based on need and zero-trust
- Most repositories in the enterprise, including data platforms, applications, and services, will be upgraded to provide superior results using vector (aka embeddings) technology over the next few years
- Most repositories now in the cloud use standards-based authentication mechanisms like SSO and OAUTH2
- That re-ranking results from even a naive, keyword-based search engine is more effective than vectorizing all data that might contain an answer to a question
By deploying SWIRL, AI solutions can use internal data for various use cases without moving data, in compliance with the security environment, and provide personalized results for each user.
How does SWIRL provide personalized AI insights?
When a user submits a query using SWIRL, the system sends the question to all the sources the user can access through their credentials. SWIRL then reorganizes the results from all the sources, identifying the most suitable and relevant ones. Since the results are limited to the user’s authorized view, the insights generated are personalized.
For example, with SWIRL, users can obtain AI summaries and answers from their personal email, calendar, and OneDrive collections—unique to them and that nobody else in the organization can typically see.
This echoes the principles for AI Infrastructure Software, where we have compliance, safety, and secure access to the data out of the box.
Get your team access to AI Infrastructure Software.
et’s have a call, and together, we can decide how to enable you to have SWIRL AI Connect for your team and organization.