Overcoming Generative AI Security and Compliance Hurdles with SWIRL

We live in the era of Generative AI (GAI), a time characterized by unprecedented advancements in artificial intelligence. GAI promises to revolutionize industries by automating content creation, streamlining workflows, and enhancing productivity. However, despite these impressive capabilities, many organizations need help to adopt GAI solutions due to security and compliance concerns.

The pain of these barriers is felt acutely in sectors where data sensitivity and regulatory requirements are paramount, and the urgency to find a solution that meets these needs is growing. Leveraging secure AI platforms like SWIRL can address these challenges by ensuring AI security and compliance best practices. As companies look to protect their data and adhere to regulatory compliance in AI development, SWIRL provides robust solutions for overcoming generative AI security hurdles.

The Pain Points of Large, Regulated Enterprises

The Pharmaceutical Industry’s Product Dossier Challenge

In the product group of a large pharmaceutical company, updating approximately 5,000 product dossiers each year is a monumental task. This process involves pulling data from dozens of sources, meticulously building dossiers, verifying their accuracy, and ensuring compliance with stringent regulations. The sheer volume of work and the need for precision and adherence to regulatory standards make this a labor-intensive and time-consuming endeavor.

The Global Consultancy’s Research Management Struggles

A global consultancy with over 5,000 individuals managing “topic areas” for research faces challenges. Each topic manager coordinates with dozens of associates across the company who contribute information. These managers are responsible for transforming this data stream into consumable insights for case teams and partners. The management of these topic areas is mainly manual, ad hoc, and expensive, often delegated to new hires who find the task unpleasant and overwhelming.

The Electronics Manufacturer’s Supply Chain Woes

In the supply chain group of a lean electronics manufacturer, staying on top of 500+ vendors and over 100,000 parts is daunting. The team, almost twice the size the company can reasonably afford, spends about 50% of its time searching for information and publishing reports on material needs. This high-pressure environment has resulted in the highest burnout rate in the company, highlighting the inefficiency and unsustainability of their current processes.

The Roadblocks to Generative AI Adoption

Many companies, including the ones mentioned above, have attempted to deploy Generative AI (GAI) solutions to alleviate these challenges. However, they found that most GAI products require hosted services or bulk data copying, which could be more practical in large, regulated enterprises. These enterprises have Chief Data Officers (CDOs) and Compliance teams whose job is to ensure adherence to various data security regulations—a role that, while crucial, often makes it challenging to leverage tools that require extensive data copying. Leveraging secure AI platforms like SWIRL can mitigate these issues by providing compliance-friendly AI solutions that do not necessitate bulk data transfers.

1. Security Risks: Generative AI systems pose security risks by potentially leaking sensitive data from training datasets, leading to data breaches. Implementing robust AI security measures, including data encryption and continuous monitoring, is essential to mitigate these risks​.
2. Data Privacy Concerns: Privacy issues in Generative AI arise from the vast amounts of personal data needed for training. Ensuring compliance with privacy laws like GDPR and CCPA requires significant resources to implement privacy-preserving techniques and protect sensitive information​.
3. Accessing Protected Data by Other Employees: Managing internal access to protected data is challenging, necessitating strict access controls to ensure that only authorized personnel can use sensitive information. Implementing sophisticated identity and access management systems helps maintain compliance and data security​.

Addressing these roadblocks can help organizations better leverage the potential of Generative AI while maintaining security and compliance. This involves adopting secure AI platforms, implementing data anonymization techniques, and continuously updating privacy policies to align with evolving regulations.

SWIRL Co-Pilot: A Practical Solution for Large, Regulated Enterprises

SWIRL Co-Pilot offers a groundbreaking approach that addresses these barriers. By leaving data in its original system of record, avoiding the need to merge or rationalize access control lists (ACLs), and minimizing additional compute and storage requirements, SWIRL presents a secure and compliant solution.

Data Residency and Security

SWIRL Co-Pilot’s ability to leave data in the system of record ensures that sensitive information remains secure and compliant with regulations. This approach eliminates the need for bulk data copying, reduces the risk of data breaches, and ensures that data governance policies are adhered to.

Simplified Access Control

Unlike vector databases, SWIRL does not require the merging or rationalizing ACLs from various systems. This streamlines access control management, allowing organizations to maintain security protocols without additional complexity.

Efficient Resource Utilization

SWIRL leverages the existing systems’ capabilities for indexing and storage, minimizing the need for extra computing and storage resources. This efficient use of resources reduces costs and simplifies the implementation of Generative AI solutions.

Seamless Integration with Enterprise SSO

By integrating with enterprise single sign-on (SSO) systems, SWIRL ensures that users only access data they are authorized to view. This integration also allows SWIRL to perform searches on behalf of users using their SSO tokens, enhancing security and user experience.

Transforming Business Processes with SWIRL

Let’s reimagine the challenges faced by pharmaceutical companies, global consultancy, and electronics manufacturers with SWIRL Co-Pilot.

With SWIRL in the Pharmaceutical Industry

With SWIRL Co-Pilot, the pharmaceutical company’s product group can streamline updating 5,000 product dossiers annually. SWIRL integrates seamlessly with their existing data sources, automating the retrieval and compilation of dossier information and moving the formerly frustrated employees into reviewers/approvers. This automation reduces the labor-intensive nature of the task, ensures accuracy, and maintains compliance with regulatory standards. The result is a more efficient, less error-prone process that frees up valuable time for the team to focus on higher-value activities.

With SWIRL in the Global Consultancy

With SWIRL Co-Pilot, the global consultancy can transform how it manages “topic areas” for research. SWIRL’s ability to maintain shared search objects curated by the topic owners makes it easy to regularly synthesize information from contributors across the company via the chosen GAI platform. This automation reduces the task’s manual, ad hoc nature, making it more efficient and less burdensome. New hires can quickly get up to speed on topics of interest, and the consultancy can deliver more timely and accurate insights to case teams and partners.

With SWIRL in the Electronics Manufacturer’s Supply Chain

The electronics manufacturer’s supply chain group can significantly improve its efficiency with SWIRL Co-Pilot. SWIRL’s capability to search and retrieve information across multiple vendor and parts databases reduces the time spent seeking information. This allows the team to focus on analysis and decision-making rather than data retrieval. By streamlining these processes, SWIRL helps reduce burnout rates and enables the company to manage its supply chain more effectively with a leaner team.

The SWIRL Advantage: A New Era of Generative AI Adoption

SWIRL Co-Pilot stands out in the Generative AI landscape by offering a practical, secure solution for large, regulated enterprises. Its key advantages include:

• Data Residency: Keeping data in the system of record ensures compliance and security.
• Simplified Access Control: No need to merge or rationalize ACLs, maintaining existing security protocols.
• Efficient Resource Utilization: Minimize additional computing and storage requirements by leveraging existing systems.
• Seamless SSO Integration: Enhancing security and user experience with enterprise SSO systems.
• Versatile Connectivity: Connecting to a wide range of Generative AI tools to leverage their capabilities without compromising data security.

Embrace the Future with SWIRL Co-Pilot

The era of Generative AI holds immense potential, but realizing this potential requires solutions that address the unique challenges of large, regulated enterprises. SWIRL Co-Pilot offers a practical, secure, and efficient way to harness GAI’s power without compromising compliance or data security. By integrating seamlessly with existing systems and streamlining access to information, SWIRL transforms organizations’ operations, enhancing productivity and innovation.

To learn more about how SWIRL Co-Pilot can revolutionize your business processes and help you overcome the barriers to GAI adoption, visit swirlaiconnect.com. Embrace the future of productivity and innovation with SWIRL Co-Pilot and unlock the full potential of Generative AI in your organization.