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.”

May is Asian Pacific American Heritage Month —a time for us to come together to celebrate and remember the important people and history of Asian and Pacific Island heritage. This feature highlights three AAPI founders from the Google For Startups community.

Read on to learn how these three founders built their businesses, leverage Google tech, and suggestion they have for aspiring entrepreneurs.

CultivatePeople 

Founder: Lola Han

Description: CultivatePeople’s compensation software, Kamsa, provides global market pay rate data and helps companies make data-driven salary decisions so they can attract and retain their most valuable asset: employees. 

Why GCP: “CultivatePeople began using GCP when integrating SSO/SAML authentication after  our SaaS product became a high priority. We were able to exceed our clients’ expectations and increase their level of trust in our platform’s capabilities. We’re currently investigating additional machine learning products, such as Cloud AutoML, that will allow us to quickly deliver exciting features.” 

Note from the Founder: “I grew up with immigrant parents who value stability and are risk-averse. My parents discouraged me from starting my own company because they didn’t want to see me struggle financially or see my health suffer (due to stress). I felt strongly about what CultivatePeople could do, so I started the company as a sole founder in 2017 and watched it double in size year over year since. While the ones I love most may not have cheered me on initially, it was important for me to hang on to the encouraging words of former bosses, executives, and founders to keep me focused on my mission. 

My advice for other AAPI founders is to be a “silent assassin” and believe in the mission and values of your organization. Always remember to stop along the way and: 

 1) Enjoy the journey by celebrating wins and giving yourself credit;

2) Follow your intuition—it’s (almost) always right; 

3) Recognize and invest in your people regularly (ie. give increases more than once a year, if warranted);

4) Give regular words of affirmation to employees on even small achievements.”

Swit

Founder: Josh Lee and Max Lim

Description: Swit is a team collaboration platform that seamlessly combines team chat with task management by allowing teams to turn their conversations into trackable tasks and share tasks to chat with simple drag-and-drop functionality, ensuring everyone is on the same page and projects get done faster.

Why GCP: “Swit is a cross-category hybrid work tool for chat and tasks. This functionality requires more complicated and heavier architecture for performance. So, configuring and managing virtual machines was really challenging to scale up our systems, while handling occasional unexpected traffic surges and frequent updates. Eventually we divided our monolithic architecture into 35 microservices when we launched our official product. The migration to GKE took around one month, and it turned out to be well worth the effort—our systems became able to offer high scalability and enough resilience to keep its uptime no matter what happened. Now we’re operating 84 workloads and 252 microservices with high stability with remarkably low downtime – less than 0.00001%/year.”

Note from the Founder: “As an AAPI founder based in Silicon Valley, I feel proud of the work ethics and diligence fellow Korean American entrepreneurs and professionals have long demonstrated here. Especially with K-pop breaking into the mainstream, I feel even more proud of our culture that strives toward an absolute perfection molded through years of training and dedication. The mission-driven culture of Silicon Valley coupled with Google’s edging technology and creativity really helped us build a product that not only encompasses verticals but also transcends cultures. Swit is growing at an unprecedented rate, and we hope  to join the long list of successful AAPI entrepreneurs here. Swit’s close network with the AAPI community wouldn’t have been possible without Google support. We are grateful for this collaborative environment, and we hope to become the next-generation ambassador for collaboration after Google.” 

Check out more from Swit in their founder story.

WISY 

Founder: Min Chen

Description: Wisy develops technology to bring digital efficiency into the physical world, supporting consumer products businesses and making them thrive in the new economy. All of us have a bad experience when we can’t find the product we want to buy. That is a $1.9T problem in the consumer-packaged goods industry that Wisy is solving with AI and analytics to help manufacturers and retailers sell more by reducing out-of-stocks and waste at a global scale.

Why GCP: “GCP has an intuitive, easy to use interface, was lower cost, and offered preemptible instances with flexible compute options. Some of the reasons why Wisy decided to use GCP include instance and payment configurability, privacy and traffic security, cost-efficiency, and Machine Learning.

Wisy has been able to advance quickly with product development, as well as collaborate better and iterate faster in the creation of our AI models, while reducing costs by 40%. At Wisy, we are solving a problem that affects everyone who shops at a store.“

Note from the Founder: “Two years ago, I moved to San Francisco to expand my second startup, Wisy. This is when I learned that my name ‘Min’ stands for ‘minority.’ I was born in China, raised in a Black community in Panama, received scholarships to attend both Carnegie Mellon and UC Berkeley. I worked for 20 years in several countries, but I have never felt so discriminated against due to my race, ethnicity, gender and age than during my time in Silicon Valley. However, this is also the place I learned that my diverse life experience is my competitive advantage. My background enables me to recruit and relate to people in different countries, create scalable and flexible products for multinational customers, and run global operations efficiently.

My recommendation to AAPI founders is to find strength in their multicultural background. Don’t hide what makes you unique, do not limit yourselves, and do not let others limit you. You will lose your edge when trading authenticity for validation. Be proud and own your story.”

If you want to learn more about how Google Cloud can help your startup, visit our Startup Program application page here and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.To learn more about how you can help #StopAsianHate during Asian Pacific American Heritage Month and beyond, visit their website here.

Operating for 23 years, Rustomjee has carved a niche for itself in the ever-growing real estate sector. Rustomjee’s portfolio includes 14.32 million square feet of completed projects; 12 million square feet of ongoing development; and another 28 million square feet of planned development. These projects span the best locations of the Mumbai Metropolitan Region. Rustomjee adds value to the lives of its homeowners through its core business, its corporate social responsibility initiatives, and its philanthropy. The business strives to ensure that every blueprint includes child-friendly spaces for parks, playgrounds, and learning rooms, encouraging families to spend quality time with each other.

In the 17 years Rustomjee’s Corporate Head of Information Systems, V M Samir, has worked with the business, it has grown from 100 employees to more than 800 employees – primarily professionals such as engineers, architects, lawyers, accountants, and regulatory consultants. The remainder work in marketing, sales, administration, security, human resources, and other associated areas.

Historically, Samir says, the real estate industry globally has lagged in embracing new workplace technologies, making building business cases, securing sponsorship, completing implementations, and encouraging adoption a difficult task.

G Suite powers cloud journey

Rustomjee started operations running an on-premises email service. However, the business wanted to upgrade its anti-spam capabilities and, in 2007, turned to G Suite. “There was no practical way I could build an anti-spam engine within that service that could match the power of the G Suite anti-spam engine and the intelligence held within its databases,” says Samir. “Our second key reason for moving was the lower cost of G Suite relative to an on-premises service that required us to spend on compute, backup, storage, and administration resources. Running G Suite would also help ensure users could still access their emails if their machines experienced an outage.”

Finally, G Suite enabled Rustomjee to access and compose emails from any location – a luxury for a real estate organization whose workers often attended construction projects with poor connectivity. “Finally, G Suite was the only service in those days that integrated calendar, meeting, and storage repositories through single sign-on. Google was so far ahead of the curve at that time and we saw the potential of G Suite to transform our communications and ultimately our business.”

“We did not have to shut down the business operations during the migration because Google Cloud Platform complemented every idea we had. And when my business users came to work on the Monday morning [after the final migration], everything was stable and the performance had improved. We told them our infrastructure had changed and they should start thanking Google Cloud!”

—V M Samir, Corporate Head, Information Systems, Rustomjee

The business started its cloud and IT modernization journey by decommissioning its on-premises email servers and using G Suite for Business. It began testing in March 2007 and went live with all production email services for 500 users in June 2008.

The intuitive nature and ease of use of G Suite made the transition seamless. “I did not have to undertake a large-scale change management exercise,” says Samir. “Users bought into the program and acquired the necessary knowledge quickly, meaning our adoption rate was extremely fast.”

With G Suite, email became the new norm to complete a range of tasks at Rustomjee. “We started exchanging CAD drawings, videos, high-resolution images, and other large files with our consultants,” says Samir. “These files had been difficult to store in on-premises environments.”

Rustomjee has improved collaboration and performance with G Suite, primarily due to four services. Gmail enables workers to communicate seamlessly externally and with each other, while Calendar enables them to set up and synchronize meetings. These meetings can be conducted through Hangouts Meet. “If a group of people internally need to discuss a work order or contract, they can coordinate calendars, sit at different locations within our organization, and collaborate using audio and video on a common service,” says Samir. “They can also work from and update a single document in Drive.”

With email and other collaboration applications running smoothly, Rustomjee saw an opportunity to enhance its technology infrastructure. The business had started operations running workplace applications on servers in small air-conditioned rooms. These servers ran databases and applications that sent data across a network to endpoints including desktops and laptops.

Expansion and the changing demands of workplace technology prompted Rustomjee to upgrade its capabilities, and the business commissioned a data center. However, Rustomjee’s continuously fast-growing compute and storage requirements, as well as the need to access new technologies to innovate and compete, quickly strained its technology model. “We required eight weeks each time we needed to add new compute and storage to our environment,” says Samir. “In addition, the heavy investments in our captive data center meant we were unable to easily leverage new technologies and decommission old technologies.”

Public cloud supports growth

Rustomjee reviewed its options and decided public cloud services could best meet its ongoing needs. “The rising cost of maintaining old hardware would force us to refresh data center technologies every five to seven years,” says Samir. “More broadly, a hardware-defined data center could not adapt quickly in the cloud-computing world, making it difficult to align compute with growth.”

The business started by moving its corporate website and microsites to a public cloud service to accommodate increased traffic delivered from a change in business strategy. “We saw an opportunity to shift our marketing and advertising from print advertising to digital platforms,” says Samir. “We wanted to be available to buyers from the point at which they start looking at properties online.”

However, Rustomjee’s digital marketing teams found it difficult to scale instances in line with demand, and work with complex user administration screens and control panels.

“With Google Cloud Platform, we’ve achieved a considerable reduction in timelines and simplified technology management and administration. All of our business users are delighted.”

—V M Samir, Corporate Head, Information Systems, Rustomjee

Google Cloud Platform presented an opportunity for Rustomjee to run its websites and microsites in a reliable, scalable, and responsive infrastructure. “Our evaluation confirmed Google Cloud Platform could support our growing demand for compute and storage,” says Samir. ‘In addition, because we undertake projects that are geographically distributed, networking – not only within the data center, but that could be accessed from any location – was very important. Only Google Cloud Platform had its own networking infrastructure.”

“More broadly, in a cloud environment, we could select any database we needed and start consuming operating systems as a service,” he adds. “In addition, we did not have to invest capital in licenses and hardware and we could always resize network bandwidth. Further, we could take advantage of pay-as-we-use cloud services, and link this to business growth.”

Google Cloud Platform also allowed Rustomjee to reduce the size of the teams needed to manage and operate its infrastructure. “When you have infrastructure running in the data center and in disaster recovery locations, you need to have a large pool of resources working around the clock to ensure constant uptime, sound backup, and good replication measures in place,” says Samir. “With the cloud, everything is simplified and we do not have to consider issues like how many hard drives have failed in on a particular morning.”

The business started testing and created its first virtual machine instance to Google Cloud Platform in April 2017. Because the Mumbai data center was not yet operating Rustomjee initially hosted its instances in the Google Cloud Platform Singapore Region. This initial move enabled the business to reduce the number of required virtual machine instances from six to one. After a year of running the website on Google Cloud Platform, the business found the simplicity of scaling compute resources meant its digital marketing teams were running more campaigns and servicing more leads, while compute spend had fallen by 56 percent. Furthermore, Rustomjee was not experiencing latency that impacted the user experience.

The opening of the Google Cloud Platform Region in Mumbai in late 2017 gave Rustomjee an opportunity to use compute, storage, and networking services located domestically. The business decided to go all-in on Google Cloud Platform and migrated a range of applications to the service.

These included an SAP enterprise resource planning system, running initially on Oracle but moved to the SAP HANA in-memory computing platform, with the assistance of advisory consultants from a leading firm. This system is integral to Rustomjee’s successful operations, meaning it has to be highly available and responsive. “All our financials are captured and stored in this system, as well as projects, materials management, order management, financial systems, and sales ordering systems, both procurement and supply-side,” says Samir. “In short, we cannot live without SAP ERP!”

Rustomjee turned to SAP specialist partner InfraBeat Technologies, a leading network implementation provider, and Google engineers to complete the migration successfully. “We were all in this together and collaborated closely to deliver the project successfully,” says Samir. “We were very impressed by the expertise and skills of everyone involved.”

A nine-day migration

With assistance from Google Cloud and the partners, Rustomjee moved all its SAP workloads, from sandbox to development, development to quality, and quality to production, in just nine calendar days, without impacting the business. “We did not have to shut down the business operations during the migration because Google Cloud Platform complemented every idea we had,” says Samir. “And when my business users came to work on the Monday morning [after the final migration], everything was stable and performance had improved. We told them our infrastructure had changed and they should start thanking Google Cloud!”

Moving to Google Cloud Platform enabled the business to complete certain customer invoicing workloads in just two hours, down from 13 hours previously. Backups of the SAP enterprise resource planning system that had taken up to six hours, were now being completed in six minutes.

“We have now fully embraced a cloud-first approach and have moved 100 percent of our workloads to the cloud. We depend totally on Google Cloud Platform to run our business.”

—V M Samir, Corporate Head, Information Systems, Rustomjee

Eight weeks down to 20 minutes

Rustomjee has also cut the eight-week cycles needed to set up the infrastructure and applications for a new real estate project, and integrate it into the SAP system, to just 20 minutes. “With Google Cloud Platform, we’ve achieved a considerable reduction in timelines and simplified management and administration,” says Samir. “All of our business users are delighted.”

With its website and enterprise resource planning system running successfully on Google Cloud Platform, the business decided to move its virtual application delivery environment into the service. “We decided to move all 800 of our employees into the cloud, so they could access applications through any endpoint, be it a mobile phone, tablet, thin client, desktop, or laptop,” says Samir.

The business decided to replace an existing application virtualization product with public images available on Compute Engine, with testing of Android, iOS and Windows operating systems across a range of devices proving highly successful. “Running the remote desktop service in Compute Engine and using public images enabled us to operate a leaner, simplified desktop as a service environment,” says Samir. “We have been able to deploy business function-specific virtual machine instances on the cloud and compartmentalize data to the business functions that need them. The business completed the move – including 8.1TB of data – in just six weeks. “The only workloads we did not move during that period were intensive workloads for visualization,” says Samir.

However, the four teams that did not use the remote desktop as a service environment – and that created visualization-intensive workloads – were working in traditional ways, compromising productivity and increasing risk. “They used to be given a desk in their respective offices and their workstations loaded with the applications,” says Samir. “There was no way of taking hourly backups of these devices and there was no recovery mechanism for the applications, because they were not in the data center.

“The other challenge was what happens to the data, because we operate out of multiple locations. The users in these four teams always had to come back to pre-assigned desks and continue working from there. This was counterproductive.”

The business subsequently implemented virtual machine instances with GPU access for visualization-intensive workloads. “We started evaluating Nvidia T4 (Tesla) GPUs in the Mumbai Region on 13 February and went live on 11 March in Mumbai,” says Samir. “By moving these 40 team members to Google Cloud Platform, we have enabled them to work with visualization workloads from any location, improving productivity and flexibility.”

Focus on core business

With Google Cloud Platform, Rustomjee can focus on running real estate projects and using technology to enable them. “I don’t have to refresh my technology every five to seven years, and I can leverage new technologies as they come on stream,” says Samir.

Reliable application access

With the flexibility and scalability of Google Cloud Platform, Rustomjee is now well-positioned to support further growth and operate in accordance with the time-limited nature of the real estate industry in India. “If we have promised to hand over the keys to a customer by a certain deadline and we fail to do so, we face a penalty of 10 percent of the cost of the project,” explains Samir. “The Indian Government introduced this regime in 2017 and business and technology have to align with its requirements.

“Google Cloud Platform is the right service to move us forward and enable us to overcome these challenges,” he adds. “We have now fully embraced a cloud-first approach and have moved 100 percent of our workloads to the cloud. We depend totally on Google Cloud Platform to run our business.”

AgroStar has launched a cloud-based mobile app that is helping to boost crop yields and encourage best practices for small farmers in India. Launched as an on-premises ecommerce platform selling farm tools in 2008, the firm turned to Google Cloud Platform (GCP) to expand its offering. It now uses cloud-based analytics and is deploying ML models to provide timely advice in five languages on everything from seed optimization, crop rotation, and soil nutrition to pest control.

A 2018 survey underscored the demand for agricultural planning for Indian farmers. While farming remains a dominant sector in India, employing half of its labor force, 70 percent of small farmers – those cultivating fewer than three acres – said their crops are damaged by unforeseen weather and pests. An even higher number – 74 percent – say they lack access to farming-related information.

Widening that gap is the relative lack of access to new, higher yield seeds and improved soil analyses for small farmers, who must otherwise rely on traditional methods. “It could take a few years for innovative information to trickle down from universities to small, grassroots farmers,” says Pritesh Gudge, AgroStar Software Engineer. “Today, just by clicking through our Android application, farmers learn about new, effective farming practices and receive advice customized to their crop and soil.”

Connecting a million farmers in the cloud

Operating in the Indian states of Gujarat, Maharashtra, Rajasthan, Orissa, Bihar, and Karnataka, AgroStar is closing the knowledge gap with a full-service, cloud-based SaaS solution – the only one of its kind in India. It combines agronomy, data science, and analytics to help farmers by providing a variety of resources.

AgroStar has reached over a million farmers through its Android app, the AgroStar Agri-Doctor. The mobile client is available as a web-based or full-featured native app. Both provide access to the firm’s knowledge base hosted on GCP, a Q&A forum that connects farmers to each other to help understand and better solve problems and to learn about innovative practices and products. Farmers can also click through to follow local and national market trends that help forecast crop prices.

In addition to the self-service knowledge base, AgroStar provides access to agronomy experts who use cloud-based analytics tools and historical data to provide season-and locale-specific advice to each farmer. “We are now tracking thousands of calls in 5 languages each day,” says Pritesh.

The AgroStar app also provides links to purchase and then track the delivery of farm tools and supplies such as cultivators and fertilizers. An in-house platform manages fulfillment centers and a doorstep delivery network simplifies the supply chain while giving farmers what they need, when they need it. By procuring directly from the manufacturers and primary distributors of farm supplies, Agrostar is achieving cost savings, which it passes on to farmers.

Build fast, pivot faster

From the start, the human and environmental variables of farming in India, not to mention the volume of AgroStar’s few hundred thousand monthly active users, made a highly scalable cloud-based solution inevitable. Farmers rely on the firm’s Agri-Doctor app to provide advice in multiple languages on topics that range widely throughout three growing seasons, each with distinct crop nutrition and rotation cycles and farm implementation requirements.

“For farmers, the focus keeps changing every month, and every season,” says Pritesh. “To serve our growing community, we needed a platform that could process images at high volume, fulfill tools and seed orders across thousands of miles, and respond to multilingual queries. We quickly moved away from spreadsheets and server-based solutions – we needed to build fast and pivot faster.”

Ending late-night deployments

The firm’s first cloud experience was with an AWS solution. At the time, AWS was the only cloud provider in India, but AgroStar wanted to find a solution that was easier to use and offered better integration with Android devices. “Deployment and processing costs were very high, and the developer tools and documentation were not as intuitive as we needed,” says Pritesh.

When GCP service arrived in India in October 2017, AgroStar embarked on a platform re-implementation that made possible dramatic changes in the way it developed and deployed its solution. Using Google Kubernetes Engine (GKE) for crop advice management and Compute Engine for its production application services, the firm built the backend for the Agri-Doctor discussion forum in only three weeks. The platform’s microservice architecture is implemented in Python and Golang and deployed on GCP.

AgroStar began to realize significant efficiencies in its build, deploy, and test cycles. “We previously needed to work overnight to deploy to production,” says Pritesh. “Now using Google for Kubernetes containers and a rolling update strategy, we can deploy during the day without any problems or interruptions to service.”

The move to GCP streamlined AgroStar’s stack. “We were running 12 independent instances on AWS,” says Pritesh. “With Google Kubernetes Engine, we are deployed on a single cluster at a cost savings of $1,300 per month and growing.”

Improving customer response times by 85 percent

With a managed deployment capability, AgroStar can devote more time and resources to executing on its platform and Agri-Doctor app development plan. A strategic goal was managing customer response times as the firm grew its base. GCP has helped the firm meet that goal, achieving an 85 percent improvement in customer response times even as traffic grew significantly.

“With our on-premises solution, we could handle around 100 customers daily, which took 30 to 50 minutes for each customer,” says Pritesh. “We now handle thousands of customers daily, taking only 4 to 5 minutes for each one.”

AgroStar used Firebase to implement its Agri-Doctor app. A real-time cloud database, Firebase provides an API that enables the Agri-Doctor advice forum to be synchronized across all its far-flung mobile clients, effectively sharing knowledge base updates with one million users in near real time.

Using cloud tools to manage and monitor

Cloud Pub/Sub, Kafka, and Cloud Dataflow manage data ingestion and queueing of event and transaction data to the analytics layer. BigQuery fetches and persists data to Cloud Storage. Cloud SQL and dashboards powered by Tableau deliver farmer crop and soil profiles within minutes.

Cloud IAM helps AgroStar control access to all its cloud resources. And Stackdriver, the integrated logging aggregation capability for GCP, helps monitor and speed debugging on every tier of the AgroStar solution.

Machine learning to enhance yields

AgroStar is developing a variety of ML components to improve responsiveness and extend its platform offerings.

To speed up the diagnosis of and treatment for crop blight, AgroStar is building a deep learning pipeline using TensorFlow. The pipeline relies on GoogLeNet models that use multi-layered convolutional visual pattern recognition. It will assess uploaded images to support a disease-detection capability on the mobile app. Based on the commercially successful AI algorithms that automated postal code processing, GoogLeNet offers improved performance and computational efficiencies by using a creative layering technique that distinguishes them from older, sequential recognition engines.

To improve its customer search experience, AgroStar is developing an ML pipeline that shrinks fetch times by suggesting tags mapped to stored data. Processed using TPUs, Cloud Natural Language and Video AI, the tags provide a metadata layer that supports queries in any of the ten natural languages that AgroStar farmers can use.

The AgroStar search pipeline consists of Long Short-Term Memory (LSTM) models of Recurrent Neural Networks. Recurrent networks exhibit “memory” through iterative processing and are distinguished from feedforward networks by a feedback loop connected to their past decisions, ingesting their own outputs moment after moment as input.

Implementing a recommendation engine

The firm is also adapting the Random Forests TensorFlow AI model to develop a crop and product recommendation engine. The model is trained by consuming numerical (rainfall, humidity, water availability per acre) and categorical (soil type, water sources) parameters to suggest appropriate products by season, region, and locale.

To simplify the product suggestion experience, AgroStar developers are testing Cloud Dialogflow, the Google Cloud conversational interface, to build a chatbot capability into its mobile app. The bot will track a farmer’s crop schedules and answer simple questions by linking to the recommendation engine.

AgroStar is also extending its analytics platform with AI-powered sales planning and forecasting. Using linear regression models implemented in TensorFlow and powered by Cloud ML Engine, the capability will enhance supply chain logistics as the company scales its operations across India.

To provide a credit on-demand offering for a range of seed-to-harvest cycle products, AgroStar is attempting to use Vision API to create an AI model that will convert uploaded photos of customer application records into standard data formats. The firm’s credit policy features a grace period in which farmers begin paying back loans after harvested crops go to market.

A versatile and friendly development ecosystem

AgroStar credits the convivial tools and documentation that GCP offers and its incremental, pay-as-you-go pricing model for both the firm’s success and its ability to manage growth.

“What Google Cloud offers is extremely good documentation and extremely simple-to-use tools and interfaces across all services,” says Pritesh. “It helped us initially deploy our platform and at every scale that we have required since then, and its cost effectiveness enabled us to staff up to meet new feature milestones.”