TeamViewer’s Strategy in the Competitive AI Model Arena

Established in 2005, TeamViewer has positioned itself as a pivotal player in the field of software development, increasingly adopting artificial intelligence technologies.

This technological evolution has enabled the company to provide clients with the capability to supervise, control, and fix various devices remotely, including laptops, smartphones, tablets, and headsets equipped with augmented reality. These capabilities are integral to IT support sectors like customer service, industrial processes, and high-tech machinery assessments.

The company’s chief product and technology officer, Mei Dent, who joined last year, managed the launch of TeamViewer’s first generative AI tool, Session Insights. This tool, introduced in October, is designed to efficiently summarize remote support engagements.

In a conversation with Business Insider, Dent highlighted the importance of teamwork within the company for integrating this AI-driven technology successfully. She remarked on the intense competition in developing superior AI models and noted that TeamViewer collaborates with third-party specialists to capitalize on their expertise.

Daily Application of AI in TeamViewer

My main responsibility is the creation of innovative solutions such as our remote connectivity and Frontline offerings.

Artificial intelligence is extensively applied throughout the company. Its use extends beyond customer-oriented products to other essential areas such as research and code examination.

Our company is built on a robust data infrastructure, strongly focusing on data security and compliance, particularly because of GDPR considerations within Germany, where we are headquartered. We've established rigorous principles to shield confidential information, shaping how AI is interwoven into our products.

A Collaborative AI Vision

The AI strategy at TeamViewer is devised through teamwork. Various departments incorporate AI in a manner suited to their distinct objectives, from marketing and sales to software development.

Our legal and data governance teams create comprehensive guidelines, yet the implementation of these frameworks is not enforced from the top down.

Introducing Session Insights

Recently, we unveiled Session Insights, an enhancement for our Remote and Tensor platforms. This tool deploys generative AI to gather and summarize support interactions in detailed written logs.

Traditionally, this information was documented manually by support personnel, a process prone to errors and inefficiencies. Session Insights automates this task, thus improving precision and saving valuable time.

Moreover, it includes analytical features to detect recurrent support challenges and contribute to creating future knowledge repositories.

Evaluating AI’s Impact

During the beta phase of Session Insights, we collaborated with our clients to guarantee clarity on its business benefits and return on investment.

While any enterprise might experiment with a language model for an initial shock effect, we aim to distinctly portray the long-term business advantages.

For instance, in the context of a client handling support through TeamViewer, the benefits manifest as enhanced productivity. How does one optimize ticket handling, and how can session summary automation maximize time efficiency?

Concurrently, for the service recipient, it’s about minimizing resolution times: Essentially, how swiftly is client satisfaction achieved?

Ensuring Data Integrity and Security

Our approach includes a multitenant cloud environment. AI operations are restricted within each client’s domain, allowing admins complete authority over AI utilization per session. Clients choose the storage parameters for their content to ensure data remains segregated.

Moreover, users receive notifications about sessions being recorded or managed by AI.

We also encrypt all content thoroughly and utilize data anonymization techniques during AI processing to safeguard personally identifiable information, even within the same organizational unit.

Partnerships for AI Development

Rather than developing AI models in-house, we adopt a multi-collaborator strategy. Our partners include renowned entities such as Google, OpenAI, Microsoft Azure, and Meta. We meticulously assess which models deliver optimal quality and cost-efficiency.