AiThority Interview with Rick Farnell, Chief Executive Officer of Tracer

Hi, Rick. Welcome to our Interview Series. Please tell us a little bit about your journey in the SaaS space. How did you start at Tracer?

Throughout my career, I’ve had the opportunity to serve as an entrepreneur, executive and operator of multiple global technology companies. I founded and scaled several companies in the data analytics and AI space, including ThinkBig Analytics, a big data analytics solutions company, and Rapid Formation, which helps incubate, fund and scale startups in the AI market. I later joined data protection company Protegrity as President and CEO, where I built upon the company’s track record of protecting critical data for the largest global enterprises. This led me finally to Tracer – then known as Appdetex – where I joined as CEO in March 2022. Since joining the company, we’ve made significant headway in transforming the businesses to meet the evolving needs of our customers. This includes rebranding Appdetex to Tracer as well as launching the next-generation of our flagship Tracer Platform and building out a global sales and marketing organization.

What is Tracer and what are your core offerings?

Tracer is the market-leading brand protection and brand success SaaS platform that leverages human-in-the-loop (HITL) AI and machine learning (ML) to continuously trace, analyze and mitigate brand misuse across global Web2 and Web3 channels. Our core product, Tracer Protect, provides real-time monitoring and analysis of IP and copyright infringement, fraud, brand impersonation, digital and digital-plus-physical counterfeiting and other forms of brand misuse. Tracer Protect automates the detection of infringing content, the classification and scoring of infringements, the correlation of bad actor networks, and the enforcement of customer directives. Brands can quickly define and customize detection criteria including brand names, search terms, trademarks and copyrighted content. Tracer Protect also enables users to create enforcement rules that can be automated for larger scalability, along with the ability to capture and timestamp infringing activity for case management and litigation.

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What does your ideal customer profile look like? What kind of customers are you planning to reach with your new AI products?

Brand protection is now a must-have line of defense for every business across the globe. However, we’ve found that the most successful brands are the favored targets for bad actors. These nefarious players will target highly successful brands by diverting customers and prospects to fraudulent and misleading digital properties – posing as the authentic brand to take advantage of unsuspecting consumers. It’s no wonder why four of the world’s top five most valuable brands trust Tracer to protect their online brand reputation and keep their customers safe from online fraud and scams.

With our new AI product capabilities, we will be able to vastly improve the time to trace (TTT), time to recommend (TTR) and time to take down (TTTD) instances of online brand misuse. While this will not change our ideal customer profile, it will allow us to better serve the evolving needs of our global enterprise customer base.

What inspired you to tap AI-as-a-service company Mad Power? What is the roadmap for the future in this acquisition?

Digital scamming, brand misuse and phishing have become increasingly invasive across all geographies, as networks of scammers seek to take advantage of businesses and their customers through online fraud and brand infringement. We acquired Mad Power Technologies because they bring a team of AI experts, developers and analysts to accelerate our pace of innovation. Using a HITL AI approach, we are able to meet the current and future needs of the global market and deliver world-class solutions to prevent online brand misuse.

With the Mad Power Technologies acquisition, we have also established a Center of Excellence (CoE) for AI and Data Science in Madeira, Portugal, which will allow us to continue developing talent in AI and software development. Since the launch of the partnership between Mad Power Technologies and Tracer, the CoE has onboarded 60 new employees dedicated to technology innovation.

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Please tell us more about the role of AI and machine learning in brand protection. How does this define new benchmarks for product and marketing teams?

Across both traditional Web2 channels and emerging Web3 channels, businesses are encountering huge volumes of sophisticated digital brand threats. Manual scanning and remediation are simply inadequate to deal with this new brand threat landscape. Using a human-in-the-loop AI approach allows businesses to achieve the scale required to identify and even prevent brand misuse – before it can damage their brands – while incorporating human judgment and intelligence at key decision points to ensure accuracy.

Going forward, product and marketing teams will be able to use our HITL AI solutions to significantly reduce the time to trace (TTT) and time to take down (TTTD) instances of online brand misuse – setting a new benchmark for success in online brand protection.

In the era of ChatGPT and generative AI, how does Tracer continue to lead the market with its breakthrough AI? Tell us more about the AI engine at the backdrop of your recent AI developments?

The Tracer Platform is powered by TracerAI, a set of advanced AI capabilities that incorporate the latest deep learning, machine vision, natural language processing (NLP), data harvesting and graph technologies to accelerate the discovery and classification of brand infringements. The platform continuously captures and filters data globally from thousands of Web2 and Web3 digital sources, including online marketplaces, NFT marketplaces, social media channels, mobile app stores, domains, websites, online advertising, paid search channels and more.

How does your HITL AI concept transform the way customers leverage brand protection software?

HITL AI combines the best of both worlds to ensure the best possible brand protection for our customers. AI and machine learning are powerful tools that are now essential to keep pace with the sophistication of today’s brand threats. However, human intelligence and decision making are required to ensure the continual improvement of AI models and algorithms to ensure greater accuracy and strong outcomes. By keeping the human in the loop, customers can easily achieve the scale and accuracy required for modern brand protection.

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ChatGPT conversations are everywhere. How do you see ChatGPT and other generative AI apps playing a larger role in your industry?

ChatGPT and other generative AI tools are game-changing technologies, with numerous beneficial applications in the enterprise. At the same time, these tools are creating a world of synthetic, computer-generated content that can flood the internet with false, fraudulent or inauthentic brand claims that can damage a business’s reputation. Going forward, enterprises will need to take great care in quickly identifying and removing any synthetic online content that has the potential to put their brand or their customers at risk.

How can companies make AI innovations more inclusive and equitable?

Ensuring that AI innovations are inclusive and equitable is a critical challenge facing companies today. Here are some ways companies can work towards achieving this goal:

• Diversify the data: AI models are only as good as the data they are trained on.
• Develop diverse teams: Companies should make a concerted effort to build diverse teams that represent different backgrounds, perspectives, and experiences.
• Implement transparency: Companies should make AI models transparent, so people can understand how they work, what data they are using, and how they are making decisions.
• Continuously monitor and evaluate: Companies should regularly monitor and evaluate the performance of their AI models.
• Provide education and training on a regular basis.
• Engage with communities working on relevant decisions affecting the implementation of AI

By adopting these strategies, companies can help ensure AI innovations are more inclusive and equitable, benefiting a wider range of the society, regardless of their background.

What is your take on AI ethics and the democratization of data science ecosystems?

Companies should embrace ethical principles in AI development, and data science tools should be made more accessible to a broader range of people, including underrepresented groups, to ensure that AI innovations benefit almost everyone. While there are groups focused on discussing ethics-related issues in AI, we have to in parallel keep evolving its adoption for the benefit of many components of society.

If invited, would you like to be part of a podcast episode on CX and B2B SaaS?

Yes, we would like to participate in the podcast.