What is AI Infrastructure Software?

Adam Haight -
What is AI Infrastructure Software?

Bring the AI to the data, not the data to the AI.

AI Infrastructure Software is an umbrella term for a software infrastructure that seamlessly integrates AI capabilities while prioritizing security, safety, and access control. 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.

This software is easily configurable and works within existing data infrastructure, minimizing the risk of data exposure. AI Infrastructure Software maintains sensitive information’s confidentiality, integrity, and availability by enforcing strict authentication, authorization, and encryption protocols. It enables organizations to leverage AI’s potential while adhering to regulatory requirements such as GDPR, HIPAA, and SOC 2, providing peace of mind to the organization and its users.

Bring the AI to the Data.

Artificial Intelligence Infrastructure Software takes a novel approach to AI deployment. Instead of centralizing data into a single repository, such as a vector database, it brings the AI directly to the data. This method ensures that data remains secure within its original systems, as the AI only accesses the necessary information when required.

By orchestrating data on-demand, AI Infrastructure Software maintains a high level of security and compliance while still enabling powerful AI applications. This approach minimizes data movement, reduces potential vulnerabilities, and allows organizations to leverage their existing data infrastructure without compromising security or performance.

AI Infrastructure Software is rapidly transforming the modern enterprise by bringing the AI to the data instead of the data to the AI. This equates to AI use cases that support seventy-five percent (75%) of the workforce and the X factor for delivering a return on investment.

Lessons learned from the first year of AI in the enterprise.

On PI Day, or March 14, 2023, to be exact, a day that also celebrates Albert Einstein’s birthday, ChatGPT 4 was announced. Astute businesses and executives quickly realized that ChatGPT could unlock levels of productivity never seen before inside their company. The simplicity of ChatGPT—ask it a question, and it knows what you mean—would be the key to unlocking corporate intelligence and rapidly transforming data literacy.

However, it quickly proved harder to deploy in the enterprise because of the private and secure nature of company data. Moreover, concerns of cloud vendor LLMs with internal data becoming compromised had companies securing their own internal versions of LLMs, like OpenAI. Most organizations already follow an “AI Inside” policy to mitigate risks.

Grounding AI with your Company FACTs.

The enterprise also quickly realized that retrieval augmented generation is the best technique for combining Generative AI with relevant company information for accurate and context-aware responses.

Using RAG to access and interact with company information and having AI-powered chatbots provide answers has become the prevailing initial use case in the enterprise, with more sophisticated companies creating AI agents leveraging existing data systems.

AI Infrastructure Software: becoming the standard.

As companies start to develop their AI ecosystem, they often face a common challenge. Tapping into information scattered across various data repositories and silos. From structured databases to communication platforms, these silos hold valuable information that can further improve Retrieval Augmented Generation (RAG). However, early adopters quickly realized that unlocking these data sources would require a new approach to enable AI in the enterprise.

A set of guiding principles emerged to address these challenges, shaping the foundation of AI Infrastructure Software. The first and most crucial tenet is “bring the AI to the data, not the data to the AI,” emphasizing the importance of leveraging existing data repositories without the need for costly and time-consuming data migration.

The second guideline states, “If your people can’t find the source of information, don’t expect the AI to be any better,” highlighting the significance of proper data management and accessibility.

Finally, the third guideline extends the concept of zero trust security to AI, treating all users, data, AI agents, and AI co-pilots equally and assuming that no entity can be trusted until proven otherwise.

SWIRL AI Connect

Solutions like SWIRL AI Connect echo the principles of AI Infrastructure Software, enabling the modern enterprise to offer intelligent applications to unlock their workforce.

By enabling intelligent applications that unlock the workforce’s potential, SWIRL AI Connect empowers modern enterprises to harness the power of AI while maintaining data security and compliance.

One of SWIRL AI Connect’s key features is its ability to bring AI to the data rather than the other way around. By enabling Generative AI to connect directly with source systems, SWIRL AI Connect eliminates the need for data migration, ensuring that data remains secure and compliant within its original environment.

This approach streamlines the AI deployment process and reduces the risk of data breaches and unauthorized access.

  • Data stays in place: SWIRL AI Connect enables Generative AI to connect with source systems, bringing the AI to the data.
  • Unified search: SWIRL AI Connect supports searching multiple data and content repositories simultaneously.
  • Adopts existing security: SWIRL AI Connect utilizes the source system security policies following a zero-trust security approach to ensure users access only what they’re allowed.
  • AI flexibility: SWIRL AI Connect supports using multiple LLMs and AIs, including company-created models located behind the firewall.
  • Data flexibility: SWIRL AI Connect supports structured data from databases, as well as content from email and office documents and applications of collaboration like Teams and Slack.
  • Pilot to co-pilot: SWIRL AI Connect enables simultaneous communication with several co-pilots simultaneously.

As the enterprise AI landscape continues to evolve, it is clear that AI Infrastructure Software will play a crucial role in shaping the future of the modern enterprise. AI Infrastructure Software, like SWIRL AI Connect, can harness AI’s power without compromising data security, compliance, or existing systems.

By bringing AI to the data and providing a flexible, scalable platform for AI deployment, solutions like SWIRL AI Connect enable organizations to unlock their workforce’s full potential and drive unprecedented levels of productivity and innovation.


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