From electrifying transportation to shifting the grid to renewable energy, environmental sustainability is one of the greatest challenges of our generation. A critical but often forgotten goal is the development of sustainable agricultural practices, especially given increasing water shortages and soil degradation around the world.

Lucent Bio was born to solve some of these threats to humanity’s ability to feed itself. It delivers crop nutrition solutions that accelerate the transition to sustainable agriculture. Lucent Bio developed novel technology for bioactive crop nutrition products, including its flagship product—Soileos®—which boosts nutrient density in crops, regenerates soil, avoids polluting agro-ecosystems, and enables the circular economy. Soileos is a plant-based product that is made by upcycling food processing co-products such as lentil and pea hulls into bioactive nutrients that then create the next harvest.

As a start-up, Lucent Bio has used Google Workspace since day one to drive collaboration, streamline operations, and scale. As an organization, it is also closely aligned with Google’s sustainability goals. Google is carbon-neutral for its operations and has made a public commitment with detailed plans to run on carbon-free energy by 2030, meaning clean power every hour of every day.

Google Workspace has been an invaluable resource to fuel collaboration between the engineers at the Lucent Bio pilot plant, the scientists at the research lab and greenhouse, and on-field agronomists as they conduct trials on Soileos across North America. Without the use of Google Workspace during the COVID 19 pandemic, Lucent Bio would not have been able to achieve their current scale.

“In just 18 months, Lucent Bio has been able to scale manufacturing from 1 kg to 1,000 kg of product per day. This year, we’re poised to take the next big step to 20,000 kg per day. During this scale-up process, we went through several iterations of improvements, resulting in a completely zero-waste manufacturing process—a hugely difficult but impressive achievement in line with our mission to accelerate the transformation of agriculture to sustainability. Every step of the way, Google Workspace has been an essential part of our innovation and growth strategy.”
Michael Riedijk, CEO Lucent Bio

Google Workspace runs on the cleanest cloud in the industry. It helps teams of all sizes, and across all industries, connect, create, and collaborate from anywhere. Workspace recently launched AI-generated summaries in Spaces, which help distributed teams stay focused while quickly catching up on chat messages they might have missed. Innovations like these keep the scientists at Lucent Bio collaborating as they build a more sustainable future for agriculture.

You can find more about Google’s commitment to sustainability here, including our goal to become not just carbon-neutral, but carbon-free by 2030, efforts to combat deforestation, and how we’re supporting clean energy.

Editor’s note: In February 2021, Google Cloud and TELUS announced a 10-year strategic alliance to drive innovation of new services and solutions across data analytics, machine learning, and go-to-market strategies that support digital transformation within key industries, including communications technology, healthcare, agriculture, and connected home. By December 2021, TELUS had completed a pilot for a use case that leveraged Google Cloud AI and Machine Learning solutions and Telco Edge Anthos to increase safety in the workplace and save lives in manufacturing facilities. The use case leverages Multi-Access Edge Computing (MEC) to move the processing and management of traffic from a centralized cloud to the edge of TELUS’ 5G network, making it possible to deploy applications and process content closer to its customers, and thus yielding several benefits including better performance, security, and customization. Today, we invite Samer Geissah, Head of Technology Strategy and Architecture at TELUS, to share how the company is delivering on its promise to use this technology to drive meaningful change, starting with workers’ well-being.

Whenever a new technology buzzword comes along I think: what problems does this solve, and for whom is this going to make a real difference? That’s because at TELUS, we see innovation as a means to act on our social purpose to drive meaningful change, from modernizing healthcare and making our food supply more sustainable, to reducing our environmental footprint and connecting Canadians in need. Multi-Access Edge Computing (MEC) is a buzzword that offers an opportunity to do just this. That’s why we want to leverage cloud capabilities and optimize our network’s edge computing potential, tapping into our award-winning high-speed 5G connectivity to help solve some of industry’s most complex challenges.

The reason why this presents such a great opportunity is that companies across industries still rely on maintenance-heavy on-premises systems to manage core computing tasks. But, with cloud capabilities delivered at the edge of our 5G network, we open a new world of possibilities for them. For example, manufacturers who currently rely on IoT-enabled equipment in their facilities can deliver new experiences by running advanced AI-based visual inspections directly from 5G-enabled devices–all without the need for local processing power or extra on-site space. In fact, it’s this example that inspired our new use case, where our Connected Worker Safety solution can be applied across a range of business verticals to help improve safety, prevent injury, and save lives, demonstrating how the perfect combination of skilled people and digital technology can make the world a safer place.

Empowering intelligent decision making at the edge

Be it a farm, manufacturing facility, hospital, or a factory floor, workers should be able to work in environments where their health and safety are held as the highest priority. But how can employers ensure that their remote, frontline, and in-office employees are safe and healthy at all times? We’ve found the answer by combining Google Cloud AI/ML capabilities and Anthos as a platform for delivering workloads, with our network’s infrastructure.

Together with Google Cloud, we have been leveraging solutions with the power of MEC and 5G to develop a workers’ safety application in our Edmonton Data Center that enables on-premise video analytics cameras to screen manufacturing facilities and ensure compliance with safety requirements to operate heavy-duty machinery. The CCTV (closed-circuit television) cameras we used are cost-effective and easier to deploy than RTLS (real time location services) solutions that detect worker proximity and avoid collisions. This is a positive, proactive step to steadily improve workplace safety. For example, if a worker’s hand is close to a drill, that drill press will not bore holes in any surface until the video analytics camera detects that the worker’s hand has been removed from the safety zone area.

A few milliseconds could make all the difference when you are operating heavy equipment without guards in place. So, to power the solution’s predetermined actions with immediate response times, we worked with Accenture and hosted the application on an Anthos bare metal Google Cloud environment running on our TELUS multi-edge access computing.

Because all the conditions in our model are programmable, this solution can be replicated at scale across a variety of practical scenarios other than factory floors. The actions in response to the analysis are also programmable, which means companies can use this technology to look at workers’ conditions and decide the best course of action to educate, assist, and protect them. All this is done through a single pane of glass ecosystem, making it easy to customize this solution to meet various business needs.

Meanwhile, leveraging our existing global networks to process data and compute cycles at the edge eliminates the need to transport data to a central location for real-time computation. This means that we can offer this solution to partners while optimizing latency and lowering costs.

Powering blink-of-an-eye communication with Anthos

To put the importance of lowering speed into perspective, consider that the average latency of blinking your eye is about 300 milliseconds. From a safety point of view, preventative processes need to be much faster than that. For this use case, our machine learning models running on edge are currently processing data at a tenth of the time it takes for you to blink your eyes, and we’re aiming to lower that latency further to help build even safer systems.

Our plan is to deploy Anthos clusters on bare metal to our customers across Canada to take advantage of our existing enterprise infrastructure, making it possible for us to run our solution closer to partners and eventually enable just one millisecond of latency.

At that point, we’ll be able to power new use cases that require near real-time feedback, leaving absolutely no room for error. This could include remote surgery, platooning of fleets on autonomous vehicles, and many other cellular vehicle-to-everything (V2X) solutions that require high-speed communication for platform operators to manage remote edge fleets in far-away places.

Improving workers’ safety while enabling new sources of revenue

Although edge computing and 5G have been around for a while, we believe that use cases like this are only just starting to demonstrate the incredible speed of change and high potential that these models provide. The next step for us is to develop our workers’ safety solution and get it to market, making TELUS an early adopter of new 5G solutions at the edge that can help our business and industry partners make workplaces safer.

It’s a great win to be able to combine efforts with Google Cloud and reduce latency in a context where timing can impact and save lives, and I’m confident that workers’ safety is just the beginning of a series of industry challenges that we’ll address together.

Job seekers can often feel lost or disconnected—like the right opportunity is out there, but they don’t know where or how to look. Employers face a similar challenge when trying to attract the right candidates. Many companies, especially large enterprises, face a talent shortage across a range of critical roles.

For global companies like Johnson & Johnson (J&J), their online career website is an important recruiting tool. It’s the “front door” for talent that could make a vital difference in the company’s future and drive innovation for years to come.

However, career sites are often underutilized. If a job seeker doesn’t find a good job match with a quick search, they will likely move on. Too often, that represents a lost opportunity for both the company and the job seeker that could have been avoided with better search results.

“Partnering with Jibe and using Cloud Talent Solution for our career site allows us to do a much better job matching opportunity to talent on a very large scale.”

—Sjoerd Gehring, Global VP of Talent Acquisition, Johnson & Johnson

While J&J receives approximately 1 million applications for 25,000 positions each year, the percent of applicants that were highly qualified for open positions was low.

Although the company always has a variety of open jobs on its career site, it noticed that even when strong matches existed between online job seekers and available positions, search results often didn’t highlight or even display the right opportunities. The user interface wasn’t intuitive enough, and job seekers couldn’t easily find their ideal positions.

As J&J began to reevaluate recruiting to take a more relationship-centric and digitally-driven approach, the company began working with Jibe, a career-site solutions provider.

Jibe introduced J&J to Cloud Talent Solution, which uses machine learning to better match job listings with job seekers’ interests and qualifications. Using Cloud Talent Solution, companies can build a compelling career-site search experience that helps candidates easily find the jobs most relevant to them. With smarter job searches and recommendations, J&J improved the effectiveness of its career site in just a few weeks.

“Jibe and Google make it easy for a large company to make a real difference in the candidate experience without investing a lot of time, money, or internal resources,” says Sjoerd Gehring, Global VP of Talent Acquisition at Johnson & Johnson. “Now that we’re using Cloud Talent Solution, our career site search results are exponentially better.”

Transforming job searches with better matches

Cloud Talent Solution better connects job seekers with jobs, because it understands the nuances of job titles, descriptions, industry jargon, and skills, matching job seeker preferences with relevant listings based on sophisticated classifications and relational models. It helps decipher job seeker queries and employer job postings, removing the manual effort of optimizing job content for search.

By using the Jibe platform to integrate Cloud Talent Solution with its career site, job seekers are more easily finding what they’re looking for and J&J is filling business critical roles more efficiently.

Since integrating Cloud Talent Solution, J&J has seen a 41% increase in high-quality job applicants per search and a nearly 45% increase in click-through rate on its career site.

“Partnering with Jibe and using Cloud Talent Solution for our career site allows us to do a much better job matching opportunity to talent on a very large scale,” adds Sjoerd. “We’re able to take a more personal approach and really connect with job seekers, which is a win.”

“Today’s job seekers expect a prospective employer’s career site to work like the other cloud services they use. Using Google’s machine learning and artificial intelligence, we can help customers like J&J get better search results and return jobs that candidates are more likely to apply to.”

—Joe Essenfeld, Founder & CEO, Jibe

Connecting people with opportunities

J&J is now offering job seekers experiences in line with what they have come to expect as consumers—searching for a job should be as easy as searching for flights, restaurants, products, and other services. Because candidates are familiar with the experience, their level of interaction and engagement goes up, creating a larger pipeline of qualified candidates and filling jobs faster.

“Today’s job seekers expect a prospective employer’s career site to work like the other cloud services they use,” says Joe Essenfeld, Founder & CEO at Jibe. “Using Google’s machine learning and artificial intelligence, we can help customers like J&J get better search results and return jobs that candidates are more likely to apply to.”

A new digital revolution for recruiting

J&J continues to work with Jibe and Google to offer new features which make its career site even more effective. By offering job seekers a transformative, engaging experience, J&J is a more attractive and visible employer, increasing the value of its brand. It’s also continuously improving its recruiting process with end-to-end visibility and feedback from interactions with a million people every year.

“Transforming our career site with Jibe and Cloud Talent Solution directly impacts our ability to attract high-quality talent and hire those candidates faster,” adds Sjoerd. “Lots of people are looking for their dream job, and if it’s here at J&J, we want them to find it quickly and easily.”

Digital technology offers increasing flexibility and choice to consumers. As a result, the retail industry is dramatically shifting toward more tailored and personalized experiences for shoppers, and businesses are rethinking how they deliver value to customers.

This couldn’t be more true for the beauty retailing industry where leading companies are turning to digital technology to create customized shopping experiences.

At Google Cloud, we’re particularly excited about our work with Ulta Beauty, the largest beauty retailer in the United States with more than 1196 stores in all 50 states, and how the company is using Google Cloud technology solutions to power personalization and redefine beauty retailing.

Established in 1990, Ulta Beauty has had incredible success as a company, and as customers become more discerning and curious about their purchases, the company is finding new ways to meet their changing needs.

Recently, leaders at Ulta Beauty recognized a huge opportunity to complement and enhance the shopping experience by helping beauty enthusiasts navigate through more than 500 brands and 25,000 products carried in their stores and online channel.

They decided to leverage the data from Ulta Beauty’s successful Ultamate Rewards loyalty program to create and offer more unique and personalized user experiences.

With more than 30 million members generating data through sales, transactions, product reviews, and social media engagement, Ulta Beauty’s Loyalty Program creates a comprehensive data set, and the company sought the right technology partner to help organize, analyze and transform that data into valuable insights for its customers.

Ulta Beauty’s leaders knew they had an opportunity to leverage data analytics and machine learning to reach customers in new ways, enhance the guest experience, and continue to grow their active loyalty member base. After considering a number of cloud providers, they chose to expand their existing partnership with Google Cloud.

“Google Cloud listened to our needs and worked in tandem with our engineering team to address our challenges,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “The ease of working with the Google Cloud team and their breadth of experience made the decision a no-brainer, laying the foundation for a great partnership.”  

In 2019, Ulta Beauty announced it was working with Google Cloud Platform to unify and organize its data, using:

• BigQuery to perform data analysis and generate dynamic content, personalized product recommendations, and event-based messages for customers.
• Cloud Storage to provide highly available, secure, resilient and cost-effective access to data across the entire enterprise.
• Compute Engine for the high-performance scalability needed to grow with customer demand while painlessly migrating existing applications to the cloud.
• Anthos to build a hybrid cloud foundation that allows their applications to take advantage of all this data, combining the power and flexibility of GKE with the ability to leverage their existing investment in secure infrastructure on-premises.

Our partnership with Ulta Beauty has enabled increased engagement with customers in store and online, and the creation of new tools and capabilities, including a new Virtual Beauty Advisor tool to deliver tailored recommendations and help shoppers choose the right products, and a Customer Conversation Platform that’s enabling deeper connections with guests, ultimately driving customer loyalty.

“It’s been a really efficient process so far due in part to the ease of working with the Google team,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “They’re experienced, approachable, and their can-do style makes for a great partnership. They listened to our needs and worked in tandem with our engineering team, figuring things out, and getting it done.”

For a business to succeed in the long term, it needs to learn not just to adapt to inevitable change, but to harness it. South Africa-based PPS has been an insurance company since 1941 and today is the biggest mutual insurance provider in the country.

As a mutual company, PPS is owned by more than 200,000 members, making them shareholders. In recent years, PPS and other companies like it have been affected by a number of external factors.

“For one thing, technology platforms have brought in a new gig economy that has all kinds of implications for insurance,” says Avsharn Bachoo, CTO at PPS. “What we’ve been seeing is basically a disruption of the South African insurance industry. We chose to see that as an opportunity.”

“Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely. To embrace the world of AI and machine learning effectively, we knew we needed a cloud-based infrastructure. We’ve found the answer in Google Cloud Platform.”

—Avsharn Bachoo, CTO, PPS

In early 2018, faced with an uncertain economic environment that was squeezing growth and profitability, PPS decided to transform itself from a traditional broker-based business into a digital insurance provider. A key pillar of this new strategy was to overhaul the company’s technology infrastructure. To turn the strategy into reality, Avsharn and his team chose Google Cloud Platform (GCP).

“Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely,” says Avsharn. “To embrace the world of AI and machine learning (ML) effectively, we knew we needed a cloud-based infrastructure. We’ve found the answer in Google Cloud Platform.”

Power, speed, flexibility with Google Cloud Platform

Previously, PPS maintained an on-premises IT infrastructure, which worked for its traditional business but was unsuited for its new way of working. In early 2018, the company started working on new products for its members but this required large amounts of compute power that proved prohibitively expensive with on-premises servers. Even existing products were starting to require more than the infrastructure could deliver. Aging equipment meant that it’s testing and quality assurance environments bore little resemblance to the actual production environment.

“We had no pre-production environments at all,” says Avsharn, resulting in more work for developers after products had been released. Meanwhile, the capital required to buy and configure more servers for new projects meant fewer resources available for innovation, and left the company less able to react to changes in the market. PPS knew it had to find a cloud-based alternative.

Shortly after devising a new digital strategy, PPS engineers attended a training session on cloud infrastructure given by leading South African Google Cloud Partner Siatik. Impressed with the presentation, PPS engaged Siatik to help run a proof of concept for a cloud-based infrastructure, running on GCP. With on-site engineers and constant communication, Siatik formed a very close working relationship with PPS. “The team at Siatik was exemplary,” recalls Avsharn. “They were well-organized, with cutting-edge technical acumen and very creative solutions to our problems. They were real game-changers.”

“We wanted the platform to retrain its models in response to new data and improve its recommendations with more information. Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically.”

—Kimoon Kim, Lead Solution Architect and Data Engineer, Siatik

The proof of concept was successful, with GCP outperforming the existing infrastructure in terms of how it handled compute demands, databases, and storage.

“It’s the speed of GCP that really impresses us,” says Avsharn. PPS saw that GCP wasn’t just an opportunity to migrate its existing infrastructure to the cloud. With Siatik’s help, it redesigned its monolithic core architecture to one based around microservices using Google Kubernetes Engine (GKE). For data processing and storage, Cloud Dataflow and Cloud Datastore proved invaluable, while Stackdriver helped the IT team stay on top of logging and monitoring the system.

“Google Cloud makes migrations very easy,” says Brett St. Clair, CEO at Siatik. “It takes care of all the hard work with configurations and replications, so when we switch the machines on, everything is ready and working.”

The ease with which PPS migrated to GCP means that it can now tackle strategic goals much more quickly than before. The most ambitious of these is an AI-powered product recommendation platform. Information is collected from customers who opt in at a defined point in their journey, this database is queried using BigQuery, and the information is fed into the platform. The AI model then calculates the most appropriate products for each member, according to their personal history.

“Most of the product recommendation engines out there are based on clustering, where you’re offered products based on your peer groups,” explains Avsharn. “For the first time, we can make recommendations to members based on their individual preferences and historical behavior. That’s really powerful for us.”

Siatik helped PPS use TensorFlow and Cloud Machine Learning Engine to build the AI platform. For the engineers, these easy-to-use tools helped speed up the process considerably, allowing them to host the models locally without any fuss. Previously, it took one to three months to manually build the model and match an offer to a customer. With the AI platform, a match takes just a few minutes. Cloud ML Engine, in particular, helped the platform adapt to new information on the fly and easily make adjustments to its hyperparameters, that is, preset variables which define the model-training process.

“We wanted the platform to retrain its models in response to new data and improve its recommendations with more information,” says Kimoon Kim, Lead Solution Architect and Data Engineer at Siatik. “Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically.”

“Google Cloud helped us cancel out a lot of the noise around machine learning and AI. We don’t have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what’s really important.”

—Avsharn Bachoo, CTO, PPS

Harnessing artificial intelligence for real-world results

PPS deployed its new AI recommendation platform in December, 2018. Just a couple of months later, its impact was clear. “In around eight weeks, we saw a 5 percent growth in sales,” says Avsharn. “It’s been a direct result of building our recommendation platform with Google Cloud. We can offer the right products to the right members.”

For developers and engineers at PPS, working with Google Cloud gives them access to high performance technology and automation options with GKE. As a result, the infrastructure runs 70 percent faster than before with fewer cores and less memory. Developers can also work in mature testing environments, and for the first time, are able to build pre-production environments, leading to better quality products. More strategically, moving to a serverless, cloud-based infrastructure has helped PPS take control of its budget, moving away from intermittent, large capital spends to more manageable, project-to-project flows of operational expenditure. The company expects to see savings of around 50 percent, or $695,000.

“We have a lot more flexibility with our resources thanks to Google Cloud,” says Avsharn. “When we have a new idea, we don’t have to outlay new capital such as servers before we can even start working on it. We just spin up instances when we want and spin them back down when we’re done.”

With the AI platform deployed and working well, PPS is already looking at ways to improve it, including real-time updates and further automation. Soon, the company will integrate the platform with more sales campaigns for more effective targeting to boost sales even further. Meanwhile, it’s also experimenting with machine learning to spot patterns in data at scale for fraud analytics and risk assessment.

For PPS, working with Google Cloud has helped it transform quickly and effectively from disrupted to disruptor. The company is now looking to gain the same transformative effects by implementing G Suite for increased productivity and collaboration.

“Google Cloud helped us cancel out a lot of the noise around machine learning and AI,” says Avsharn. “We don’t have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what’s really important.”