At Arpeely, we’ve developed some of the world’s most advanced advertising technology. Our machine learning (ML) media acquisition platform and “win-win” business model enables customers to bring highly intentful users to their offerings with precision, peace of mind and minimal overhead.

Real-time bidding is a dynamic and intricate process that involves buying and selling ad impressions in milliseconds. Each time a user opens an app or website, advertisers or ad-tech companies acting on behalf of advertisers have milliseconds to bid on ad spaces in real-time auctions, and the highest bidder wins the opportunity to display their ad. This is where Arpeely comes in, leveraging advanced algorithms, innovative UX and funnels to optimize the bidding process and maximize performance for advertisers.

At Arpeely, we use various signals often not used by traditional competitors to outperform the market and zero-down on high-intent and soon-to-be loyal users. For example, in advertising a mobile app, we predict, based on real-time conditions and user context, the user’s likelihood to make an in-app purchase many weeks into the future.

As for the ads themselves, gone are the days of simple banners; today’s ads are “mini products” that captivate and engage users. We employ a wide range of ad formats that go beyond industry standards. Our ads can be immersive videos, compelling messages, interactive experiences like mini-games or mini-apps, or even a multi-step mixture of all of the above. By integrating logic and interactivity, Arpeely enables users to engage with the ad content seamlessly and gauge user intent without leaving their main activity.

Our business model dictates that we don’t get paid if our advertiser doesn’t get paid. We like to say that our algorithms, like water, can trickle into hidden market opportunities missed by the rest of the industry that uses less granular tools. These and other capabilities make Arpeely a strategic partner in the challenging space of media and user acquisition.

Innovation at the edges of data science and engineering

Today, we handle millions of impressions per second and over a billion ML predictions daily. We are directly connected to seven of the world’s largest real-time bidding exchanges, including Google AdX. We also work very closely with our clients, ranging from prominent startups to companies in the S&P Top 20.

Daily, we tackle complex engineering and data challenges on multiple fronts. On the engineering side, we ensure that every real-time auction receives a lightning-fast response within a strict 150ms timeframe. On the data side, we fire multiple ML predictions per auction and ingest TBs of data daily. On the user-serving front, we serve A/B-tested assets across a long tail of geos and devices, with even the slightest fluctuations in load speeds affecting business dramatically.

Right from the start, we knew we couldn’t do it alone when it came to building our technology stack. When you look at available platforms, it’s clear Google Cloud has a robust architecture that is easy to manage, use and scale, especially for our use cases. They also have reliability and feature completeness which are critical in our line of business.

Under the hood

Building upon Google Kubernetes Engine (GKE), we run multiple services that handle our main bidding flows. We utilize Golang for services that run at a large scale and Python for when we prioritize development speed, community and readability. All of these can reach an immensely high scale, which is managed and monitored automatically in GKE. Communication between these services and our Redis (our Google Cloud partner) cluster happens in sub-millisecond latency over Google Cloud’s strong network infrastructure and enables us to run complex real-time logic for every impression.

Once we have tackled the actual bidding, we are left with the challenge of streaming our data into BigQuery for analytics and model training. We utilize a mix of Cloud Pub/Sub, Memorystore and Cloud Storage to create a mechanism capable of ingesting many TBs per day in near real-time without compromising on cost. Real-time data is critical for a company like Arpeely to test and reiterate at a fast pace.

BigQuery is our data warehouse for operational analysis and is an essential part of our business. We use it both as a warehouse, for large-scale computations and in an operational capacity that closes the loop between production, data, and ML retraining. A team of two or three people can manage petabytes at scale with minimal maintenance.

On top of these, we’ve built a state-of-the-art in-house model pipeline suited specifically for ad-tech industry purposes. It allows us to effectively deploy complex solutions — on-the-fly calibration, flexible conversion steps, sampling of heavily imbalanced data sets, adjusting weights, and A/B-tested model deployment and more.

Google Cloud also offers us an entry point for several very useful built-in products that have become deeply embedded in our daily stack and routine. Among them are Operations Suite (formerly Stackdriver), Cloud Profiler, Cloud Storage, Cloud CDN, Cloud SQL, Memorystore, Cloud Scheduler, Error Reporting, and more.

In addition to all the technology, there’s also a human touch. Google’s skilled Customer Success team possesses a unique blend of technical expertise and business acumen, acting as strategic advertisers and opening doors we did not know existed.

Opening the door to the future of advertising

Standardizing on Google Cloud enables us to focus our resources on innovation and growth. Instead of having to research business solutions and invest time integrating disparate technologies, we can tap into a wide range of Google Cloud tools as needed. Thus, it is crucial that we set up a good technological foundation and prepare for future growth of the business.

Google Cloud enables us to focus our resources on innovation rather than our infrastructure. This means we can put more effort into finding ways to match clients with high-value customers and grow their revenues. Even though online advertising has been around for over 20 years and pioneered by Google itself, Google Cloud gives us the impetus to disrupt the market and deliver greater levels of value to our customers today and in the future. 

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

Check out the Redis listing on Google Cloud Marketplace. Please give it a try and let us know what you think!

The COVID-19 pandemic continues to push the healthcare and life sciences industry in entirely new ways. In record time, we’ve witnessed public health officials, vaccine developers, equipment manufacturers, and essential workers take life saving actions—regularly putting their own lives at risk—to respond to the exceptional challenges of our time. 

Yet after all the turmoil and uncertainty of the pandemic, record breaking levels of investment continue to come into the market to fuel innovations. 

Vaccine development is now measured in weeks rather than years; providers are leveraging telehealth technologies to improve the physician and patient experience; and individuals have embraced a variety of devices to assume greater ownership and control of their personal health. 

With that in mind, here are five of the many innovations I see driving healthcare and life sciences for at least the next 12 months: 

1. Unleashing the power of healthcare and life sciences data

People have arguably never had as much access and understanding to their personal health data than they can in 2022. They have the ability to understand their genetic makeup, medical history, family history, and activity levels to ensure they are living a healthy lifestyle. Taken together, this longitudinal profile can become the basis for more personalized medicine. Add wearable devices to the mix and patients gain real- or near-real-time updates on their health status. 

Further, global regulatory agencies have continued to mandate the need for providers to maintain a longitudinal health record that provides a holistic view of the patient across all the encounters they have had with a health system. Physician surveys conducted by the The Harris Poll and Google Cloud show that a 360-degree view of the patient, across all provider encounters, leads to faster, more accurate diagnosis, and better outcomes. 

If secure data access and interoperability can begin to include insurers, researchers, public health officials, and others in the field, the powerful network effects benefiting patients will only grow. When combined with those longitudinal phenome profiles, the opportunities for personalized and preventative medicine enter a whole new era.

2. Healthcare and life sciences M&A boom continues

Although the pandemic initially slowed activity on mergers and acquisitions in the early part of 2020, the healthcare and life sciences industry has seen a rapid rebound and acceleration of deals ever since. The success of COVID-19 vaccines, the importance of telehealth, and the focus on molecular modeling and genomic-based drug development have all boosted investment as organizations look to enter new markets, develop new therapies, and leverage low interest rates while they last. 

In 2021, the total funding of US digital health startups surpassed $29 billion across 729 deals, according to advisory Rock Health. That’s almost double the levels of 2020, which itself set records. Analysts at PWC meanwhile estimate M&A investments in biopharmaceutical and life sciences could approach $400 billion this year across all sub-sectors

Clearly, the pandemic has been a primary driver of investment as the focus on healthcare has dramatically increased. Yet the increased activity also reflects changing business models and emerging technologies that are now required to compete in the rapidly evolving space. For organizations to capitalize on these investments, it will take not only great vision and intellectual property but also the right technologies—like cloud—and the right data interoperability models, to make partnerships and acquisitions more scalable, feasible, and seamless.

3. Transforming the patient experience at a new rate

The pandemic has shined a spotlight on the inefficiencies and complexities that exist in healthcare markets across the globe. As wave after wave has surged, global healthcare systems remain overwhelmed on most every aspect of patients’ treatment journeys. Even before COVID-19, healthcare was already one of the largest spend areas for governments around the world. The pandemic has only exacerbated the known issues. 

Clearly, administrators, regulators, physicians, nurses, and patients would agree that the processes and models need to change. There’s a need to maintain this momentum and even increase the tempo to achieve lasting change.

Take telehealth. Within months of the start of the pandemic, providers moved to provide more remote capabilities so physicians could still meet with patients virtually to ensure health and safety on all sides. Payers recognized the importance of telehealth and began to update reimbursement rules. And organizations are now reimagining policies in areas such as prior authorization, submission, and adjudication to reduce complexity and bureaucracy while improving responsiveness.

Looking beyond the system, organizations are also recognizing and deepening their understanding of the structural and social determinants of health that impact patient care and health outcomes, especially for historically underserved communities.  Private and public sectors are learning from, and increasingly partnering with, the social sciences, public health, biomedical informatics, computer science, public policy and community groups around how to build a mI’ore equitable and inclusive consumer products and Health IT strategies. 

The newfound levels of transparency, visibility, and accountability that patients, caregivers, and organizations are achieving will ultimately increase competition and provide a more effective, equitable, efficient and, above all, healthier marketplace for all patients. As we move past the worst of the pandemic, regulators and organizations should keep fighting for progress over business as usual.

4. AI is now a core competency for Drug Development

The ability of organizations like Pfizer, Moderna, Johnson & Johnson, and Astrazeneca to develop COVID-19 vaccines has been a remarkable accomplishment—particularly the historic speed with which they were created and deployed. This innovation acceleration was largely enabled by the use of new drug development platforms that allow researchers to use artificial intelligence and machine learning to model protein and cellular interactions to rapidly advance the science.

No longer must researchers rely on traditional laboratory testing (and retesting). With their improved understanding of the molecular and genetic structure of a patient and, for example, their tumor, researchers can use AI to enable simulations on computers rather than testing in live conditions. This technology can process thousands, even millions of simulations to help  identify high-potential candidates for treatment consideration and subsequent analysis. 

AI-enabled drug discovery models can eliminate months and years from the research process, which can reduce the time to develop a drug and accelerate the time to treatment for an individual patient. As just one example, consider the work on AlphaFold2 by Google’s DeepMind unit who leverages AI to predict effective protein shapes for new drugs. Healthcare and life sciences organizations already recognize the potential of AI. Now comes the investments to leverage this rapidly evolving technology to support their efforts now and in the future.   

5. Ecosystem partnerships tackle complexity and spur innovation

As the importance and growth of the healthcare and life sciences industry continues, we will see even more new players and partnerships emerging to address old problems in new ways. This trend will touch all aspects of the healthcare value chain and will, increasingly, see three- and four-player partnerships emerge to address the complex challenges of today’s healthcare marketplace.

Technology will continue to play a key role as capabilities and platforms will transform all aspects of the marketplace. Cell phones, wearable devices, and other technologies will provide real-time updates and notifications to patients on everything from glucose levels to payments for healthcare services. Voice recognition software will document physician and patient discussions to reduce the burden of record keeping. Real-world data will be used to simplify and confidentially recruit patients for participation in clinical trials. 

New players will continue to enter the market to improve health outcomes and reduce costs. Major retailers are among the companies extending their pharmacies to provide additional diagnostic and concierge services, saving patients from additional appointments while boosting prevention. Community organizations are emerging to help identify and care for underserved communities whose health outcomes are significantly lower than the average patient. 

For all the exhausting and heart-wrenching challenges of the past two years, the opportunities the pandemic has laid bare cannot be overlooked. We owe it to those who have worked and fought so hard for every life to forge even more new partnerships—and make it easier to do so—so that the next crisis, when it does arise, will never be as bad as the one we’re now conquering. Technology can be the enabler in this effort and help bring us together to continue to conquer the challenges that lie ahead.