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Mike Davie, Founder & CEO at Quadrant – Interview Series




Mike Davie, is the Founder & CEO of Quadrant, an Appen company that provides location data and location-based business solutions that are fit for purpose, easy to use, and simple to organize. Quadrant’s proprietary Geolancer platform provides authentic, accurate, and up-to-date Point-of-Interest data, manually verified on the ground. For mobile location data, the company observes over 450 million unique devices per month which helps companies understand patterns of movement in the real-world. Quadrant also offers a blockchain-based Consent Management Platform for app developers and publishers who seek GDPR and CCPA compliance.

Could you discuss the genesis story DataStreamX, a pioneering data acquisition and transaction platform?

In the early 2010s, tele-communication companies were looking at future technologies and ways to monetize and commercialize Long Term Evolution (LTE) data. There was an infrastructure need to handle real-time data feeds at mass, upwards of 50 billion connected devices. After working at Samsung, I recognized the demand for this type of platform and created DataStreamX.

DataStreamX eventually evolved into Quadrant, a blockchain-based location data platform. What was the inspiration at the time to parlay blockchain into this system?

In 2017 while working with a big telecom company and transacting billions of data sets, we would see the same data coming from different parties. Each party confirming that they had the rights to sell the data. This obvious fraud and deception caused us to solve this problem. We wanted to know where the data originated from and create a system to trace the data origin. Blockchain enabled us to understand where data comes from and where it goes; people who supply the data can understand where it goes, and people who buy the data can get clarity on where it comes from.

Could you discuss some of the AI tools that Quadrant offers that helps customers better use location data to target the right audience?

The Quadrant Platform is designed to host a wide variety of potent Artificial Intelligence (AI) algorithms that enable businesses, government agencies and organizations to use Quadrant’s high-quality mobile location and POI data to support a variety of location intelligence use cases, such as mapping and locality-based advertising and recommendation engines. Our AI tools are options for clients, who don’t have their own algorithms or partners, to get started with the data quicker and speed up the analyze process. Researchers, universities, and startups often want these tools to help get them started. We provide raw location data to allow our clients to do what they need to do and take pride in enabling our clients.

For example, with Quadrant Geofence Query, users can set a customized geofence around real-world locations – such as restaurants, airports, public venues and shopping malls – to obtain the Ad-IDs of distinct users that fall within the specified area. Quadrant’s Geofence Footfall Query returns the daily football within a specified geofence and can be used in multiple scenarios, from retailers looking at how to increase the footfall to physical stores to authorities assessing traffic patterns to urban developers researching targeted areas. Quadrant’s Nearest POI Model, a machine learning model, identifies the nearest Point of Interest for a given location based on the latitude and longitude values. It enables users to analyze and understand traveling habits, identify time and speed taken to travel from one POI to another, and identify routes frequently taken between two POIs.

Could you describe in what ways Quadrant believes that innovations in location data can make the world a better place?

Geospatial data, including POI data, is used across many essential industries, including in last-mile delivery, food delivery, supply and logistics for brick-and-mortar and online shopping, real estate, ridesharing, mapping and navigation. COVID-19 has made accurate location data even more important in many of these areas as consumers and businesses change how they interact and rely more heavily on delivery services. Movement patterns that were understood before the pandemic no longer apply, and companies are trying to figure out exactly what this means. Up-to-date geospatial data ensures businesses can adapt to these changes and continue to provide fast delivery of goods and services, while reducing waste (time, gas, etc.) and minimizing delays and inaccurate deliveries that frustrate customers and can disrupt supply chains.

Accurate geospatial data also enables government agencies, essential services providers such as healthcare agencies and organizations, and businesses such as retail and restaurant chains and banks to streamline their services and keep pace with rapid population growth and re-urbanization around the world. For example, up-to-date location data can help a government agency find the optimal sites for new train stations, an educational institution plan new campus facilities, and a small business optimize where it grows. The types of data these organizations rely on become outdated very quickly, so the ability to keep data fresh is essential to understanding changing population patterns and serving constituents effectively.

Location data has been particularly valuable to retail and restaurant businesses, which were forced to adapt quickly to lockdowns and shelter in-place orders and will need to be able to rapidly assess the impact of re-openings, which are occurring in fits and starts. As a result, the demand for accurate, up-to-date location data will continue to soar.

Population movement is another area where up-to-date geospatial data is critical. Governments and urban planners must understand how to expand or contract infrastructure and services to meet rapidly shifting demands, especially for transportation and healthcare. Only the combination of accurate and up-to-date geospatial data and mobile location data can make these trends visible and provide the required actionable insight.

Could you elaborate on Quadrant’s mission of transparent data use, and what that it entails?

Quadrant conducts stringent evaluations on our suppliers to ensure authenticity and quality, and we scrub our data to detect and eliminate data corruption and duplication. Equally important, we conduct regular audits to make sure our data is collected and processed in compliance with the relevant data privacy regulations, including GDPR, CCPA, and PDPA.

Quadrant also offers a compliant, privacy-first app monetization platform. As privacy regulations tighten around the world and non-compliant data becomes worthless, Quadrant’s SDK comes with an integrated and free Consent Management Platform, QCMP, which does not collect any personally identifiable information (PII) and leverages an immutable blockchain ledger of the consent lifecycle, which is readily available for compliance audits. This ensures a worry-free revenue stream. QCMP also tracks evolving privacy legislation around the world and automatically adds new compliance requirements.

In your view is the future of geolocation/geospatial data?

Both long-term trends and recent events, especially re-urbanization, growing concerns around data privacy, and the pandemic, are driving innovation in both mobile location data and POI data. For POI data, a desperate need for accurate and up-to-date datasets has driven us to go beyond the idea of web scraping or crowdsourcing data to building a new, proprietary data collection platform, which includes Geolancer, a custom-built smartphone app, and the corresponding backend infrastructure.

Using the mobile app, freelance Geolancers can add POIs manually on the ground and periodically verify them while walking around in their neighborhood. This provides the most up-to-date and verified information to data buyers while also helping small, local businesses be seen.

For mobile data, evolving privacy regulations, such as GDPR, and changes to Apple and Google app policies will eventually lead to a point where data sourced without explicit user consent will be unusable in many countries. This has led to the need for consent management platforms, which we have already built. Our QCMP uses blockchain technology to track data back to the source and provide a real-time audit trail, so customers can secure their revenue stream while ensuring compliance.

Appen Limited (ASX:APX), recently announced that it has signed a definitive agreement to acquire Quadrant, what will this mean for the future of the company?

Appen collects and labels images, text, speech, audio and video used to build and continuously improve the world’s most innovative artificial intelligence systems. The company has expertise in more than 235 languages, a global crowd of over 1 million skilled contractors, and the industry’s most advanced AI-assisted data annotation platform.

The acquisition will enable Quadrant to integrate Appen technology with our high-quality mobile location data technology suite, strongly positioning the unified business to deliver permissioned high-quality data for organizations that rely on geolocation for their business, both in day-to-day operations, as well as in developing AI models. As part of Appen, we will also enable our clients to solve bigger and more complex problems.

Is there anything else that you would like to share about Quadrant?

Geospatial data has increased in value, especially with the pandemic. All industries are seeing a need for POI data from financial analysis, economic development, last mile logistics, and more. Our clients understand how geospatial data works in the real world and are implementing solutions that require both geospatial and POI data. We will continue to see this increased interest as the pandemic leads to more permanent lifestyle changes.

Thank you for the great interview, readers who wish to learn more should visit Quadrant.

A founding partner of unite.AI & a member of the Forbes Technology Council, Antoine is a futurist who is passionate about the future of AI & robotics.

He is also the Founder of an investing website, the generative AI platform, & is he is currently working on launching a platform that will offer users the ability to configure and deploy autonomous agents by breaking prompts into sub-tasks.