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For today’s public-facing employees, managers are challenged to equip their staff with the complex and ever-changing information they need to serve visitor needs. And behind the scenes, it can be difficult to train skilled workers to execute complex procedures and follow compliance regulations. “Everyone’s role is increasingly complex,” says Atif Kureishy, Founder and CEO of Vistry, a leader in conversational AI. “Workers need to have access to real-time information, or be fluent and knowledgeable in a very specialized domain.”

Employers deal with their own issues, too, as they look for innovative ways to optimize labor spend in the face of economic headwinds and a complex operational landscape. Generative AI chat assistants can help solve these problems for employees and employers alike.

Generative AI Tools at the F1 COTA

Vistry’s AI Chat Staff Assist deployment at the Formula 1 (F1) Circuit of the Americas (COTA) in Austin, Texas is a powerful example of the value of such solutions.

With 450,000 attendees and 10,000 staff members, the sheer scale of the COTA event was a challenge in itself. It was difficult to answer visitor questions on topics as varied as ticketing, transportation, schedules, and facilities. Working with COTA officials and their IT partners, Vistry customized the ZenoChat gen AI chat assistant, which staff members accessed via their mobile devices.

The #GenerativeAI model was trained using event-specific #data to ensure accuracy, and was equipped with a multilingual user interface to facilitate communication between employees and visitors. @vistryai via @insightdottech

The generative AI model was trained using event-specific data to ensure accuracy, and was equipped with a multilingual user interface to facilitate communication between employees and visitors. The solution enabled real-time responses to queries—enhanced by third-party mapping software to help workers provide directions to guests and navigate the sprawling venue themselves.

The results pleased both COTA leadership and staff. Vistry’s AI platform was able to handle hundreds of distinct queries over the course of the three-day event. Even with questions becoming more frequent and complex, workers continually grew comfortable with the tool. The result was greater efficiency—and less stress than in previous years. As one staff member put it, the AI assistant “turned potential chaos into orchestrated excellence.” Event organizers, for their part, found that the AI chatbot increased employee preparedness and enhanced guest experiences.

AI Chat Use Cases in Life Sciences

AI chat solutions offer clear benefits in a wide range of vertical segments and use cases. In life sciences manufacturing, for example, customized AI assistants can support workers in laboratories or on the factory floor. These employees need real-time access to information—often stored in extensive, inaccessible documentation—to ensure that they follow the proper chemical manufacturing and control protocols and meet the compliance requirements of regulatory bodies.

A well-trained AI tool can help manufacturing, quality assurance, and R&D teams find answers to their bill of material (BOM) questions, explore and understand the dependencies between their raw materials suppliers and suppliers of other types of components and equipment, and access other detailed information they need to do their jobs.

Achieving compliance with REACH, OSHA SDS, and GHS regulatory frameworks is essential for life sciences firms to ensure safety and operational success. The ZenoChat platform offers a powerful solution by creating a knowledge graph of compliance information, automating documentation processes, and enhancing competitive analysis. As a result, life sciences firms can streamline compliance efforts, reduce errors, and stay ahead in a competitive industry while ensuring they meet all regulatory standards.

Of course, in industries where accuracy and precision are paramount, the risk of an “AI hallucination,” a type of bug in which generative AI tools offer incorrect information with deceptive certainty, is a major concern. But Kureishy says it’s possible to improve the accuracy of AI chat assistants for such use cases. “Our models are based on a retrieval-augmented generation (RAG) architecture to ground their responses in a far more limited and trustworthy set of enterprise data and are combined with knowledge graphs to further improve the accuracy and relevance of replies.”

The result is an AI model that minimizes the risk of hallucinations found in other LLMs—and that can be made even more reliable via a system of checks and validations.

AI PCs and Software Toolkits Enable Edge Deployments

While RAG-based architectures improve accuracy, they still don’t address the other major concern of industrial enterprises: data security. For use cases that involve sensitive intellectual property, even the generally robust protections of a cloud-deployed model can constitute an unacceptable risk.

This is one reason Vistry makes it possible to run its AI chat tools entirely at the edge—a deployment mode that owes much to the company’s technology partnership with Intel.

“We were very excited to see how easy it was to deploy a RAG-based system at the edge running on an Intel AI PC,” says Kureishy. “Intel^® Core^™ Ultra processors are amazingly performant, even when working with GPU-intensive inferencing workloads that these AI models require.”

In addition, Vistry used the Intel^® OpenVINO^™ toolkit to optimize its AI models for edge deployment while still delivering the speed and accuracy required to preserve user experience.

The ability to deploy AI chat assistants completely at the edge allows highly risk-averse users to take advantage of these solutions. And beyond that, it supports businesses that operate in remote locations, where connectivity is an issue—giving every enterprise a way to ensure continued service in “disconnected” mode in case of an IT outage.

Unlocking the Value of Unstructured Data

In the years ahead, more and more organizations are likely to turn to AI tools to help their employees increase efficiency and productivity—in part because there are simply so many sectors in which workers need fast, accurate answers to their questions.

“The expectation is for a person to be able to consume unstructured, document-oriented information readily, but when that information has proliferated and is settled in various content management systems, there’s a real gap: one we’ve all lived, personally and professionally,” says Kureishy. “AI assistants finally give employees easy, real-time access to all of that information—and that’s going to be incredibly valuable for a lot of businesses.”

This article was edited by Georganne Benesch, Editorial Director for insight.tech.