Building a strong brand in today’s hyper-competitive business environment takes vision. It also requires a flexible, easily managed approach to digital asset management (DAM), so marketing professionals and other stakeholders can easily share, store, track, and manipulate assets to build the brand.

Many of today’s leading companies, including JetBlue, Slack, TripAdvisor, Lyft, and HealthONE, rely on Brandfolder to deliver consistent, organized, and efficient brand experiences. Brandfolder provides an easy-to-use platform that can scale across an entire company with little end-user training, empowering customers to distribute digital assets wherever they are needed. Customers also gain much greater insight into how those assets are used, and how to use them more effectively in marketing campaigns and brand messaging.

“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform.”

—Ajay Rajasekharan, Head of Data Science, Brandfolder

Brandfolder is constantly advancing its development efforts to introduce new data-driven features without complicating the user experience. Big data, artificial intelligence (AI), and machine learning (ML) are key to meeting customers’ unique business needs, and essential for Brandfolder to compete in the fast-moving DAM industry. To enhance these capabilities, Brandfolder sought a public cloud provider that could help it scale its data pipeline cost effectively while providing access to advanced AI technologies.

After graduating from the Techstars startup accelerator program in 2013, Brandfolder tried two other cloud providers before standardizing on Google Cloud Platform (GCP).

“We saw a difference with Google Cloud from the very beginning because the interactions felt like a strategic relationship,” says Jim Hanifen, Head of Product at Brandfolder. “Google gave us startup credits and a lot of face-to-face support, which we hadn’t experienced with other cloud providers. We decided to move our entire infrastructure to Google Cloud Platform.”

Building an ML platform for brand intelligence

After performing an initial lift-and-shift migration of virtual machines (VMs) onto Compute Engine, Brandfolder built an ML platform using GCP managed services to seamlessly deliver its data products. The platform leverages Cloud SQL, Cloud Storage as the data lake, Cloud Dataproc for cloud-native Apache Spark computing clusters, Cloud Composer as the batch job scheduler, Cloud Pub/Sub as the backbone data pipeline, Container Registry to store Docker images, and Google Kubernetes Engine (GKE) as the application orchestrator. Cloud Dataflow brings data into the data lake and into BigQuery for analysis.

“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform,” says Ajay Rajasekharan, Head of Data Science at Brandfolder, who describes the architecture in a detailed blog. “We simply ingest raw application and event data on one end and output an ML service on the other.”

“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost. We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”

—Brett Nekolny, Head of Engineering, Brandfolder

For many general use cases, Brandfolder does not need to build custom ML models, and instead relies on pre-trained API models from GCP. For example, it uses Vision API and Video Intelligence API to auto-tag creative assets on import to enable fast, intuitive searches across images and videos. When more product- and brand-specific modeling is required to address unique customer use cases, Brandfolder builds and trains custom ML models using its GCP pipeline or Cloud AutoML, a suite of products built on Google transfer learning and neural architecture search technology. For example, if a Brandfolder customer makes different types of grills, Brandfolder can use AutoML Vision to train a model to recognize the different grills.

“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost,” explains Brett Nekolny, Head of Engineering at Brandfolder. “We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”

Industry-leading security and performance

Google Cloud’s security model helps Brandfolder give existing and prospective customers peace of mind that their data will be protected. Cloud Identity & Access Management (Cloud IAM) provides enterprise-grade access control, while Cloud Identity-Aware Proxy (Cloud IAP) enables remote users to work more securely without the hassles of a VPN client. GCP also isolates cloud resources into projects, making it easy to assign permissions and keep data and VMs organized and segregated.

“With Google Cloud, everything begins and ends with security, which makes things very easy for us,” says Jim. “If we’re under a security review, we can submit a Google security white paper. If a potential customer has security concerns, we tell them we are hosted on GCP, and those concerns go away.”

To give customers even better application performance for accessing their brand assets, Brandfolder uses Cloud Memorystore, an in-memory data store service for Redis, to cache data and provide sub-millisecond data access for production applications.

“It was much easier for us to use Cloud Memorystore versus running Redis on our compute instances,” says Brett. “The high availability, replication across zones, and automatic failover with no data loss are big for us.”

Global private network interconnects between Google Cloud and the Fastly content delivery network (CDN) dramatically reduce latency, allowing Brandfolder’s customers to deliver and update even very large creative assets quickly around the world.

“What’s beautiful about the relationship between Google and Fastly is that if one of our customers uploads a new version of an asset, we can propagate that out to Fastly, and the new version will automatically show up in all the places where it’s referenced,” says Brett.

“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter. Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”

—Jim Hanifen, Head of Product, Brandfolder

Improving employee and customer productivity

Brandfolder also uses Google solutions for real-time collaboration and productivity, using G Suite to connect employees with intuitive, cloud-based apps. Teams use Gmail, Calendar, Docs, Drive, Sheets, Slides, and Hangouts Meet every day to move the business forward. Many of Brandfolder’s customers are also G Suite users, and Brandfolder offers a plug-in that allows them to view their creative assets inside of Docs and pull images in as needed. Customers can also log into Brandfolder with their G Suite credentials, making the solution even easier to use.

“We’ve been using G Suite since the beginning, and it’s helped us collaborate efficiently to build a successful, growing company,” says Jim. “Our teams expect to have that kind of close collaboration, and everyone here enjoys the G Suite experience.”

Driving 99 percent annual business growth

With automated tagging and other innovative AI-based features, Brandfolder is helping customers locate and distribute assets faster. As a result, Brandfolder is building customer loyalty and increasing sales, growing its business by 99 percent year-over-year. Since moving to GCP, Brandfolder has been able to scale its analytics and data pipeline 50x without a corresponding increase in costs and has not had to expand its development team.

“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter,” says Jim. “Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”

EyecareLive transforms the healthcare ecosystem with Enhanced Support, a support service from the Google Cloud Customer Care portfolio.

Telemedicine is now mainstream. It exploded during the COVID-19 pandemic. A 2022 survey by Jones Lang Lasalle (registration required) found that 38% of U.S. patients were using some form of telemedicine. This number is expected to grow as consumers are demanding more convenient and immediate access to care, and doctors are seeking efficiencies, cost savings, and to forge closer relationships with patients.

But because the eye-care field is so heavily regulated, optometrists and ophthalmologists face more technical hurdles to perform telemedicine than their peers in other medical practices.

To join the telemedicine revolution, a generic technology solution wouldn’t do. Eye-care professionals need a more carefully architected and rigorously secure platform – one that ensures a very high degree of compliance and privacy.

EyecareLive provides exactly that. Their comprehensive cloud-based solution was built specifically for eye-care telemedicine practices. They not only facilitate telemedicine visits with patients via video, but help providers stay in compliance with complex industry regulations.

What’s more, EyecareLive is the only platform in the industry that conducts vision screening using Food and Drug Administration (FDA)-registered tests to check a patient’s vision before connecting them to a doctor through a video call. The doctor can thus triage any issues immediately and quickly determine the right next steps for proper care. In addition, their platform digitally connects optometrists and ophthalmologists to the entire eye-care ecosystem, including other doctors for referrals, insurance companies, hospitals, pharmaceutical firms, pharmacies, and, of course, patients.

On top of all of this, the automated back office for their eye-care practices processes electronic health records (EHRs), clinical workflow, billing, coding, and more into one platform. EyecareLive streamlines operations and frees up doctors to focus on delivering the highest possible eye healthcare and on building stronger relationships with patients.

“Considering the number of plug-and-play services that Google has built into the Google Cloud Healthcare solutions, Google is basically supporting the entire healthcare industry from an infrastructure provider point of view.” — Raj Ramchandani, CEO, EyecareLive

Seeking greater agility, EyecareLive migrated to Google Cloud

EyecareLive is truly cloud first. They had operated entirely in the AWS cloud since opening their doors in 2017. Several years in, they decided to look for an additional cloud provider with broader support for digital health platforms. They specifically wanted to migrate to one they could rely on to deliver plug-and-play services, which would accelerate innovation of their platform. Rather than re-architecting for a new cloud, EyecareLive wanted a cloud platform that would offer compatible services they could use to meet their needs for reliability and availability.

“If we want to deploy a new conversational bot or build AI models that assist doctors to diagnose based on a retina image, Google Cloud provides these services which are reliable and tested by Google Cloud Healthcare solutions in many cases.” — Raj Ramchandani, CEO, EyecareLive

Versatility was another requirement. The EyecareLive platform must fulfill the demands of a variety of organizations — doctors, pharmaceutical companies, clinics, and others. EyecareLive also has an international deployment strategy that goes far beyond offering a domestic telehealth solution. Therefore EyecareLive needed a cloud functionality that extended into the broader global eye-care ecosystem.

EyecareLive chose Google Cloud. The most compelling reason was the deep industry expertise found in Google Cloud for healthcare and life sciences. This distinguished Google Cloud from all other possible cloud providers considered by EyecareLive. “We like Google Cloud because of the differentiations such as Google Cloud Healthcare solutions, computer vision, and AI models that can be used out of the box,” says Raj Ramchandani, CEO of EyecareLive. “We found these features more robust for our use cases on Google Cloud than any other.”

“Google is heavily into its Healthcare Cloud. That’s what differentiates it. We love that part because we can tap into innovative healthcare cloud functionality quickly.” — Raj Ramchandani, CEO, EyecareLive

Key to production deployment (and beyond): Google Cloud Enhanced Support

As a cloud-born company, EyecareLive had an exceedingly tech-savvy team. But the migration was a complex one that involved migrating third-party software and networking products that were tightly integrated into EyecareLive’s own code. The team knew it needed expert help with the migration. What’s more, doctors, patients, and other users required 24/7 access to the platform, and any interruptions to availability or infrastructure hiccups during the migration would disrupt their online experiences. However, the EyecareLive team was already stretched by continuing to grow and innovate the business, so they asked Google Cloud for help.

EyecareLive purchased Enhanced Support, a support service offered by the Google Cloud Customer Care portfolio. Specifically designed for small and midsized businesses (SMBs). Enhanced Support gave EyecareLive unlimited, fast access to expert support from a team of experienced Google Cloud engineers during the intricate, multifaceted migration.

“It was my top priority to engage Google Cloud Customer Care to help us keep the platform always available for our doctors and users,” says Ramchandani. “The level of detail to the answers, the clarifications of having the Enhanced Support experts tell us to do it a certain way has been enormously helpful.”

For example, one of the valuable features delivered by Enhanced Support is Third-Party Technology Support, which gives EyecareLive access to experts with specialized knowledge of third-party technologies, such as networking, MongoDB, and infrastructure. This meant all components in EyecareLive’s infrastructure could be seamlessly migrated to Google Cloud, and afterward EyecareLive could lean on Enhanced Support experts to continue to troubleshoot and mitigate issues as necessary.

“The response times to the questions and issues we had when going live was fantastic. It was the best experience with a tech vendor we’ve had in a long time.” — Raj Ramchandani, CEO, EyecareLive

With Enhanced Support at their side, EyecareLive was able to get up and running quickly in preparation for their international expansion by using Google Cloud’s prebuilt AI models, load balancers, and networking technologies that were designed to be easily deployed across multiple regions throughout the globe. “We know exactly how to implement data locality to scale our deployment into different regions and into different countries, because we’ve learned that from the Google Cloud support team.” — Raj Ramchandani, CEO, EyecareLive

EyecareLive then proceeded to rapidly scale their business, knowing that Google Cloud would ensure they could meet compliance standards in whatever country or region they expanded into.

“Since we’ve moved to Google Cloud and chose Enhanced Support, we’ve had 100% availability. That’s zero downtime, which is incredible.” — Raj Ramchandani, CEO, EyecareLive

Enhanced Support also provided the capabilities for EyecareLive to:

• Resolve issues and minimize any unplanned downtime to maintain a high-quality, secure experience for doctors and patients during and after migration
• Acquire fast responses to questions from technical support experts
• Learn from guidance from the Enhanced Support team beyond immediate technical issues

EyecareLive builds momentum toward their vision for eye-care telemedicine

By working closely with the Google Cloud Enhanced Support team, EyecareLive was able to successfully migrate their platform.

“If you ask any of my engineers which cloud provider they prefer, they’d all respond ‘Google Cloud,’” says Ramchandani. “The documentation is there, the sample code is there, everything that we need to get started is available.”

EyecareLive was then able to go on to grow and scale their business in the cloud in the following ways:

• Successfully managed a complex migration with minimal disruption and maximum availability, ensuring a consistent, secure, and compliant-ready experience for doctors and patients
• Gained the trust of both doctors and patients – they know that EyecareLive protects their sensitive medical data
• Kept EyecareLive agile and focused on innovating forward rather than building new features from scratch by supporting the team as they took advantage of Google’s tailored, plug-and-play technologies
• Analyzed performance over time to plan for future growth by partnering with Enhanced Support for the long term

“We know we can rely on Google Cloud from a security point of view. We love the fact that Google Cloud Healthcare solution is HIPAA compliant. Those are the things that make us trust Google to do the right thing.” — Raj Ramchandani, CEO, EyecareLive

With Enhanced Support, EyecareLive sees a bright future in the cloud

With the help of Enhanced Support, EyecareLive brings digital transformation to the eye-care in the healthcare industry by integrating the entire ecosystem of eye-care partners onto one platform making EyecareLive a leader in their industry.

Learn more about Google Cloud Customer Care services and sign up today.

As community and business concern over global warming, sustainability, and energy security continues to rise, companies such as Bharat Light & Power (BLP) are working on answers.

Founded in 2010 and located in Bangalore and Delhi, BLP is one of the leading clean energy generation companies in India. According to Tejpreet Singh Chopra, Chief Executive Officer of BLP, the business started with the aim of delivering clean energy from renewable sources such as wind, solar, biomass, and hydro to the 300 million residents of India that did not have reliable access to power at that time.

However, BLP soon began experiencing problems ensuring availability of the wind turbines that powered utility-scale wind power generation across the country.

“While we were investing large amounts building wind farms, the failure of the smallest component could shut down an entire wind turbine and compromise our efficient operation,” says Chopra. “A $5,000 battery could fail and shut down a $2.5 million piece of equipment!”

BLP transformed its legacy thinking about man, machine, technology, and process, and implemented an AI and Internet of Things (IoT) project. The business used hundreds of tags from its wind turbines to capture and send machine behavior and performance data to a control center. This data triggered an 18-month project to create AI and machine learning algorithms that would enable engineers to predict component failures in wind turbines, improve generation, and adjust maintenance and replacement schedules accordingly.

This activity provided the foundation of a technology business—one of the three companies that comprise BLP—that delivers enterprise AI for industrial uses over a platform, branded Orion.

“We provide an end-to-end solution that enables businesses in industries such as transportation, logistics, ports, infrastructure, oil and gas, supply chain manufacturing, steel, and automotive to improve productivity,” says Chopra.

As the business expanded, it began to extend beyond its core “AI for industry” mission. It recruited an IoT team to help factory owners and operators enable the programmable logic controllers (PLC) and supervisory control and data acquisition (SCADA) systems that run disparate equipment and machines—such as production line machines of different ages and countries of origin—to talk to each other and provide usable data and insights.

Agility and adaptability key

BLP’s management team realized early that the business needed to be agile and adaptable to keep pace with changes in technology.

“We knew we would have to effectively destroy and remake the business every 18–24 months to remain relevant, so we needed a service that could support our dynamic infrastructure, data, and AI needs,” says Chopra.

The business started operations on a cloud service but quickly ran into problems. “We found in the world of industry—the vast amounts of data, the variety of sources of data, and the complexity of insights required—created a very different set of challenges relative to the consumer technology environment,” says Chopra. “Our cloud provider could not provide an architecture that made sense for an industry-focused solution.”

Google Cloud to power AI and visual analytics

Within two years, BLP advanced its strategy and focused on using open source to reduce the cost of its architecture. As Orion matured and its take-up grew, the business began looking at multinational cloud services to run the forthcoming version 3.0 of the platform.

BLP found Google Cloud provided the best fit for its needs for a range of reasons, including the ease of use of Google Cloud services—likened by the BLP technology team as “the equivalent of a consumer app experience”—and its high quality database services, high availability, fast response times, and the power to run the platform’s AI and visual analytics.

BLP established as its key objective a 20% reduction in costs over its previous cloud service and availability levels exceeding 99.9%. The business completed the deployment in June 2019 following discussions and input from Google Cloud’s engineering and architecture experts prior to and during the first stage of the project.

Cloud IoT Core—a managed service that allows organizations to connect, manage, and ingest data from dispersed devices—is the cornerstone of the architecture supporting the latest latest version of the Orion platform, Orion 4.0. BLP has also created a data pipeline based on Cloud Pub/Sub event ingestion and delivery and Cloud Dataflow data processing.

Cloud Bigtable provides a high-performance NoSQL database service for the platform’s analytical workloads and BigQuery delivers a powerful analytics data warehouse. Cloud Functions enables the business’s developers to build event-driven serverless applications.

This architecture currently captures, processes, analyzes, and reports on 8 million data points in 578 turbines around the world per day and processes data from 200,000 data points in 4,000 sensors per day.

The Google Cloud architecture supports the data visualization and reporting and the AI and machine learning-powered products created by BLP. These reports and products enable users to monitor remote assets and use AI-based analytics to predict machine failures before they occur, sequence failure events, and maximize equipment uptime.

A range of benefits to customers

With Google Cloud, BLP is delivering projects with a range of benefits to customers, including increasing manufacturing productivity by at least 5% and reducing costs by about 10%.

“We’ve enabled one of the largest electrical companies in India to compare production line performance by capturing data from PLC and SCADA systems and extracting it to Google Cloud for processing, analysis, and reporting,” says Chopra. “For another customer, we’ve deployed an IoT system that has saved them about $200,000 in energy costs over six months.”

The business is also providing monitoring, reporting, and analysis to predict likely failures of gearboxes, bearings, generators, and blades in 2,000 wind turbines—that provide close over 2 GW of wind power—in countries such as France, Germany, Italy, India, Portugal, Spain, the United Kingdom, and the United States.

Furthermore, BLP is providing visual analytics to help one of the largest ports in the world detect when workers are not wearing helmets or safety equipment.

“We also do a lot of inventory track-and-trace work to help companies improve supply chains and help factories keep track of tooling through Bluetooth low-energy technologies,” says Chopra.

With Google Cloud, BLP is now ideally placed to execute its business strategy of helping customers improve productivity and increase growth, control and reduce costs, and enhance quality and safety.

“We are realizing this strategy by working to become the best company in the world at using AI to predict machine failure,” says Chopra. “Our underlying technology strategy entails enabling the most advanced IoT hardware used by industry to talk to software and the cloud, using the most powerful AI cloud around—which is why we chose to marry our AI algorithms with Google Cloud—and delivering insights through visualization.”

Testing Edge TPU

The business is now testing Edge TPU to run AI at the edge in high-performance, small-footprint, and low-power ASIC environments.

“We think that will be the next big revolution as TPU costs come down,” says Chopra. “It will be a considerable benefit performing AI at the edge rather than involving the full infrastructure of the cloud.”

BLP is keen to build on its existing relationship with and use of Google Cloud to further transform manufacturing worldwide.

“Manufacturers are pushing the boundaries of quality and cost through initiatives such as Lean Six Sigma, Zero Defects, poka-yoke, just in time, and other methodologies and approaches,” says Chopra.

“The next wave of manufacturing improvements are coming through industry 4.0, AI, IoT, and Google Cloud’s analytics, databases and other services. These are ideal to power this change in the industrial world.”