Near Intelligence, Inc.

Hello, and welcome to NEAR Intelligence's first quarter 2023 earnings call. This is Gwynne Lauber with NEAR, and with me on today's call are Neil Matthews, Neil's Chief Executive Officer, and Rahul Agarwal, our Chief Financial Officer. Our earnings press release was issued this afternoon and is posted on our website. The primary purpose of today's call is to provide you with information regarding our first quarter 2023 performance and offer an outlook for our second quarter and full year 2023. Certain statements made on this call that are not historical facts, including those related to our future plans, objectives, and expected performance are forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. These forward looking statements represent our outlook only as of the date of this conference call. While we believe any forward looking statements made on this call are reasonable, actual results may differ materially because the statements are based on our current expectations and subject to risks and uncertainties. These risks and uncertainties are discussed in our filing with the SEC. You should refer to and consider these factors when relying on such forward-looking information. Any forward-looking statement made speaks only as of the date on which it is made, and we do not undertake and expressly disclaim any obligation to update or alter our forward-looking statements, whether as a result of new information, future events, or otherwise. except as required by applicable law. I encourage you to visit our investor relations website at investors.near.com to access our first quarter press release, SEC reports, and the webcast replay of today's call. During the course of today's call, we will refer to certain adjusted financial measures. We use these non-GAAP financial measures to review and assess our performance and for planning purposes. These non-GAAP financial measures should be considered in addition to, not as a substitute for or in isolation from, GAAP measures. Additional information about these non-GAAP measures, including a reconciliation of non-GAAP to comparable GAAP measures, is included in our press release. Finally, unless otherwise stated, All financial comparisons on this call will be made to our fiscal year 2022 results on a historical basis. And with that, let me turn the call over to Anil.

Welcome, everyone, and thank you for joining us today. Let me start with our financial highlights. First quarter, revenue was $15.5 million, slightly above the high end of our data. Net revenue retention for the quarter continues to be greater than 100% and came in at 110% well within our quarterly expectations. Notwithstanding on target revenue growth, we continue to sharpen our focus on the path to profitability. Against our planned adjusted EBITDA, we have delivered a better than expected adjusted EBITDA of negative $7 million to one. This should further improve our year-end adjusted EBITDA realization. The results of our quarter support our belief that as budgets tighten, companies continue to spend on products that deliver ROI. Because our solutions provide insights that help our customers to make better decisions and to more effectively utilize their budget, we believe our customers will continue to subscribe to our solutions as They helped them to understand which programs had a positive impact on the bottom line. Now, additionally, one question has come up in all my meetings. What are we doing with generative AI? The AI is not new to NEAR. It's a part of the foundation that our products are built on. And generative AI should help us develop even more advanced solutions in the future. It's a natural compliment to over 10 years of our learning and innovation. Now, I'd like to talk to you about NIRS products and our strategy for the future. Today, NIRS solutions are built on three pillars, data, privacy, and AI. Each pillar enhances the others, making our solution better. Let's take the first pillar, which is data. Data is what we understand. It's what we built our initial business on over the past decade. Data is what sets me apart from other companies because we believe that we have high-quality, proprietary, large-scale data that is unmatched. You've probably heard me say that data is the jet fuel that you need to train your AI model. Data is what helps us realize a vision of truly helping organizations make better decisions. While other companies talk about the scale of the data and how fast they're growing the data, NIR is investing heavily in data quality and the depth. We believe we have enough data. Our focus now is on providing our customers with the highest quality data, making it even more useful to them. We believe that we can further improve the quality of our data by embedding AI models in the pipeline to clean the data. The second pillar of our foundation is privacy. Clearly, you cannot aspire to be a leading, trustworthy, global data company without having made significant investments in privacy and driving a lot of innovation through our work on privacy. Our products are built with privacy-led design to provide the largest source of intelligence in people, places, and products. Being in compliance with local regulations everywhere our customers' business is crucial for the leading company, and our customers take comfort in knowing that we work every day to ensure that our privacy-built solutions are in compliance. In our industry, privacy is a stable state. The third pillar is AI. We've been leveraging machine learning and AI in our platform and products for the past decade. Many of you have seen this work demonstrated in our AllSpark platforms, where we use natural language to query people and their behavior across places and product categories. In 2016, this was groundbreaking because it allowed our customers and partners to seamlessly access our large repository of consumer data using natural language. With the development of generative AI, we are even more excited about NEOS opportunities because we think we'll be able to add more value to the work we do for our customers and to be even more differentiated from our competitors. We look at generative AI as a significant platform and shift that'll have profound impact on many industries, including our own data industry. We also believe that it will uncover a chasm where our proprietary data will be a major competitive depreciator as we believe we'll be able to train our models not just to help our customers discover insights, but also to fill in the knowledge gaps while protecting privacy. NEOS' three pillars, data and AI, underpinned by privacy, provide us with a solid foundation today. But it's the convergence of our high-quality proprietary data with generative AI in an ever-changing regulatory compliance landscape which we believe will give us an even greater advantage in the future. What is important? At Near, our goal is to maximize data utility while protecting privacy. We are driving innovation to make sure that our customers get maximum value out of data. We believe our high quality data coupled with generative AI will put an end to having to choose between the value of data and compliance. We believe that we have the tools that will, in the near future, allow our customers to be privacy compliant without sacrificing the insights that the beta delivers. Generative AI should allow us to break the traditional model and to fill in the gaps so that we are able to not only be privacy compliant, but to provide valuable insights to our customers. Moving on to our quarterly results, a significant part of our go-to-market strategy is our focus on landing and expanding within our customers. We have had much success by starting with a small deal with a customer in one geography or division and then expanding the relationship over time. We were able to do this by providing solutions that exceed their expectations. On the last call, I mentioned the large European retailer who started working with us a few years ago with a small subscription to our platform. They had just renewed the contract with us for an eight-figure, one-year subscription. That's a great example of a land and expand strategy. Building on that experience during the quarter, we also signed a new customer, Aldi, one of the top supermarket chains in the world, in partnership with Cold Spirit Media. The customer will use Nino to drive football traffic into their stores and measure the effectiveness of their campaign. NEAR solutions will allow them to get a better understanding of the appropriate catchment area for each store and help them attract prospects and customers. In the first quarter, one of our customers, one of the world's largest commercial real estate services and investment firms, renewed its contract with NEAR with a three-year extension for its Canadian unit. In its United Kingdom unit, the customer renewed its subscription and expanded the relationship by adding on a second product. In time, I believe we will continue to expand our footprint with this customer. During the quarter, we also expanded our relationship with a tourism partner to offer more insights to his clients across New York State. Due to high demand, they continue to expand the number of points of interest we have to offer to the New York client. Through its relationship with Near, the partner can better understand tourist visitation trends, providing its customers with insights at a more granular level. In the U.S., we signed a partnership with a leading digital marketing platform built for travel marketers. The customer's platform uses artificial intelligence and travel data to provide multi-channel marketing solutions that drive visitors to destinations. NEAR's insights will help them deliver deeper reporting on the impact of digital marketing programs for their customers, which will in turn help those destination marketers measure and prove their impact to their stakeholders. As you know, NEAR is a global company. Beyond its large customers in Europe and North America, we also have a large presence in APAC. One of those customers is Yahoo Australia, and we recently expanded our multi-year relationship. Since beginning their relationship in 2020, Nia has expanded into additional geographies that Yahoo serves. Nia's solutions serve as a measurement tool for Yahoo APAC properties, helping the customer to demonstrate increased value across its online properties. Recently, we also closed our largest single contract in Southeast Asia with Admatic Malaysia. This is a leading digital media company in Southeast Asia that works with some of the region's largest brands. Again, this is a three-year deal in partnership with a minimum commitment well into seven figures. Another exciting aspect of MIR is the broad array of challenges that we help to get our customers soft. For example, in the U.S., we recently worked on a study with the county of Kauai and several government agencies to help them understand tourist moments throughout the county. Our goal was to deliver real-world insights that would provide information that would help transportation planning on the island. The insights will help them to understand resident and visitor travel patterns, identify intuitive solutions for reducing traffic conditions, and contribute to planning for a more sustainable quiet. Here is a global company. I believe our land and expand strategy is working, resulting in larger deals and longer contracts. In the end, our success will be driven by our ability to deliver on our promise to consumers that our proprietary data is safe and our promise to enterprise customers that they can be privacy compliant while maximizing the insights that the data delivers. We believe that we will be able to achieve both because of the strong foundation that we built on our three pillars, data, privacy, and AI. As a leading trustworthy global data intelligence company with a history of innovation, we will continue to build products with privacy-led design and to provide our customers with the largest source of intelligence on people, places, and products.

Now I'll turn the call over to my colleague, Rahul Agrawal.