If you’ve been exploring recently-launched consumer generative AI tools like Bard and thinking about how to build similar experiences for your business, Generative AI App Builder, or Gen App Builder for short, is here to get you started.

Gen App Builder is part of Google Cloud’s recently announced generative AI offerings and lets developers, even those with limited machine learning skills, quickly and easily tap into the power of Google’s foundation models, search expertise, and conversational AI technologies to create enterprise-grade generative AI applications. 

“Google Cloud’s leading AI technology enables STARZ customers to discover more relevant content, increasing engagement with, and the likelihood of completing the content served to them,” says Robin Chacko, EVP Direct-to-Consumer, STARZ. “We’re excited about how generative AI-powered search will help users find the most relevant content even easier and faster.”

Gen App Builder is exciting because unlike most existing generative AI offerings for developers, it offers an orchestration layer that abstracts the complexity of combining various enterprise systems with generative AI tools to create a smooth, helpful user experience. Gen App Builder provides step-by-step orchestration of search and conversational applications with pre-built workflows for common tasks like onboarding, data ingestion, and customization, making it easy for developers to set up and deploy their apps. With Gen App Builder developers can: 

• Build in minutes or hours. With access to Google’s no-code conversational and search tools powered by foundation models, organizations can get started with a few clicks and quickly build high-quality experiences that can be integrated into their applications and websites. 
• Combine the power of foundation models with information retrieval to find relevant, personalized information. Enterprises can build apps that understand user intent via natural language, and surface the right information with associated citations and attributions from a company’s public and private data. They can also fully control what data their applications access and the content or topics they want to address.
• Build multimodal apps that can respond with text, images, and other media. Gen App Builder supports not just text, but also other modalities such as images and videos. It allows developers to build apps using a combination of text and images as inputs to find information across documents, photos, and video content, enabling richer customer interactions. 
• Combine natural conversations with structured flows. Developers can granularly blend the output of foundation models with controls to ground answers in enterprise content, and step-by-step conversation orchestration to guide customers to the right answers.
• Provide the ability to transact and connect to third party apps and services. Gen App Builder makes it simple to create digital assistants and bots that not only serve content, but also connect to purchasing and provisioning systems to enable transactions from the conversational UI, and escalate customer conversations to a human agent when the context demands.

A new generation of conversational AI experiences and assistants 

Consumers of enterprise applications expect to interact with technology in a seamless, conversational way to quickly find the information they need and act on it. Gen App Builder can help reinvent these customer and employee experiences by ingesting large, complex datasets that are specific to your company–from websites, documents, and transactional systems like billing and inventory, to emails, chat conversations, and more. These AI-powered apps can synthesize information across all of these sources to provide specific, actionable responses, using only the data you have provided. 

Some of the most popular uses are in customer service, where generative apps can contribute to increasing revenue, customer satisfaction, and customer loyalty. For example, if a retail customer reaches out to modify an order, a virtual agent can help them change it to another product. The customer doesn’t even need to provide the new product name—they can just upload an image and let the agent guide them through the rest. Watch this demo to see how a retail chatbot can use multimodal capabilities to help a consumer navigate various options on the website, including giving the customer ideas on how to use the product and even helping them complete the purchase with the ability to transact within the conversational UI. This scenario could apply to multiple industries and use cases, ranging from consumer goods and public services, to finance and internal corporate systems like intranets.

Combining the power of Google-quality search with foundation models

Finding the right information from data across the organization is a critical requirement within any enterprise. Yet it can be challenging to build high-quality enterprise search experiences with existing tools. Current systems struggle to understand user intent, are difficult to implement and customize, and don’t provide a high-quality user experience. 

One of the most exciting features of Gen App Builder is the ability to combine the power of Google-quality search with generative AI to help enterprises find the most relevant and personalized information when they need it. With Gen App Builder, enterprises can build conversational search experiences across their public and private data in minutes or hours with no coding experience. 

Enabling multimodal search across text, images and video within the enterprise is a key aspect of the search experiences in Gen App Builder. In addition to providing high-quality search results, Gen App Builder can conveniently summarize the results and provide corresponding citations in a natural, human-like fashion. Gen App Builder also automatically extracts key information from the data and enables personalized results for users. Watch this demo to see how these capabilities can come together to transform the search experience for employees at a financial services firm. The ability to integrate Google-quality search within the enterprise’s applications means they can enjoy a new level of data utilization, drive increased process efficiencies, and provide delightful experiences to their employees and customers.

“Customers have been shopping at Macy’s for generations. Being able to deliver 360° personalization and contextual recommendations will help ensure that Macy’s is still providing future generations of shoppers with a seamless, exceptional experience,” said Bennett Fox-Glassman, Senior Vice-President, Customer Journey, Macy’s. “We’ve already realized an increase in revenue per visit and conversion rates had great success using Google Cloud’s AI technology and are looking forward to exploring how these latest announcements bring together Natural Language Processing and Generative AI capabilities to deliver next-gen search and conversational experiences for our customers.”

The ability to intuitively interact with complex data across a variety of sources allows organizations to better serve their customers and deliver more relevant offerings. Combined with conversational and fulfillment abilities, the potential for improving customer engagement and employee productivity is immense. We’re excited to see how developers and enterprises use a mix of these capabilities to power new experiences and revenue opportunities.

If you’re interested in a closer look at the Gen App Builder, tune into this session at the Data Cloud & AI Summit. Take a step forward to getting hands-on and join the waitlist for our trusted tester program. And finally, bookmark our generative AI landing page to keep abreast of the latest news, updates and possibilities from this exciting new world of Gen Apps.

We are thrilled to announce that Google has been named a Leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report. For more than a decade, BigQuery, our petabyte-scale cloud data warehouse, has been in a class of its own. We’re excited to share this recognition and we want to thank our strong community of customers and partners for voicing their opinion. We believe this report validates the alignment of our strategy with our customers’ analytics needs.

“Customers like Google’s frequency of data warehouse releases, business value, future proof architecture, high-end scale, geospatial capabilities, strong AI/ML capabilities, good security capabilities, and broad analytical use cases,” according to the Forrester report. Today’s data leaders require a data warehousing platform that provides both depth and breadth and with BigQuery, organizations are able to unlock deeper data science and machine learning capabilities while promoting data democratization and providing the highest levels of availability. 

Google BigQuery: 5 out of 5!

Forrester gave Google BigQuery a score of 5 out of 5 across 19 different criteria, including:

Today, customers across the globe use BigQuery to run business critical analytics workloads to enable BI acceleration, IoT analytics, customer intelligence, AI/ML-based analytics, data science, data collaboration, and data services. Customers such as Verizon, Wayfair, HSBC, Twitter, AirAsia, KeyBank, The Home Depot, and Vodafone have anchored their digital transformation efforts on BigQuery—unlocking deeper insights for their people. 

Customers use BigQuery across all industries, to solve issues like credit card fraud detection, predictive forecasting, anomaly detection, log analytics and many more. Forrester recognized this work and gave BigQuery a 5/5 score for supporting vertical and horizontal use cases. 

More BigQuery advantages 

Google is the first hyperscale provider to offer a multi cloud data analytics solution. With BigQuery Omni, customers can perform cross-cloud analytics with ease, and drive business outcomes they couldn’t achieve with the siloed approach offered by other vendors. 

We designed BigQuery to be highly scalable and more open and interoperable so that customers can join data across SQL databases, traditional unstructured data lakes in object storage, and even spreadsheets using any analysis tool. 

Recent innovations like BigQuery BI Engine lets us provide the best analytics experience by delivering sub-second query response times from any business intelligence tool, from Google’s Looker and Connected Sheets to Tableau, Microsoft Power BI, ThoughtSpot, and others. Our goal is to meet customers where they are rather than force them into a one-size-fits-all approach to data analysis. 

With BigQuery, organizations gain both breadth and depth of capabilities to transform their analytics strategy. Forrester also gave BigQuery 5 out of 5 in:

Data-powered innovation 

These advantages enable our customers to accelerate their digital transformation and reimagine their business through data-powered innovation. Google’s leadership across AI, analytics, and databases comes together in a single data cloud platform that provides everyone with the ability to get value out of their data faster.

We bring decades of research and innovation in AI to our customers through industry-leading AI solutions, that in turn helps our customers solve their biggest problems. Our support of open standards and APIs enables interoperability between a variety of services for ingestion, storage, processing and analytics across the data cloud platform. And finally, we believe our multi-layered security approach throughout the data stack ensures redundancy and reliability so that customers can have the peace of mind that their data is always protected. 

We are honored to be a leader in this Forrester Wave™ and look forward to continuing to innovate and partner with you on your digital transformation journey. 

Download the full Forrester Wave™ :Cloud Data Warehouse, Q1 2021 report. And check out these smart analytics reference patterns. To learn more about BigQuery, visit our website, and get started immediately with the free BigQuery Sandbox.

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.

It’s no secret that many organizations and job seekers find the hiring process exhausting. It can be time consuming, costly, and somewhat risky for both parties. Those are just some of the experiences we wanted to change when we started Gyfted, a pre-vetted talent marketplace for people who complete tech training or degree programs and are looking for the right career move. At the same time, we’re helping businesses save time and improve recruiting outcomes with our automated candidate screening and sourcing tools.

Our vision is clear: To take a candidate through one structured hiring process, and then put them in front of thousands of companies. It’s similar to the common app system in higher education. Sounds simple, but it is a herculean technical and UX task. To succeed we had to combine advanced psychometric testing, machine learning, the latest in behavioral design, and develop the highest quality structured, relational dataset to represent candidate and manager profiles and preferences on our network. Fortunately, we were cofounded by world-leading experts in these areas including Dr. Michal Kosinski, one of the world’s top computational psychologists, and Adam Szefer, a gifted young technologist. We’ve been joined by a group of equally talented employees, most of whom work remotely in Poland, US, Switzerland, UK, Israel, and Ukraine.

The influence of dating platforms and matching

When seeking inspiration, we were influenced by the success of dating platforms, especially Bumble with its focus on commitment. These platforms have done a great job using design to match people together.

We like to think we’re doing the same for recruiters and candidates in terms of not only role and culture fit matching, but also through a fundamental feature of Gyfted, which is that our job-seekers are anonymous. This helps recruiters meet one of their goals today, which is to minimize bias in the hiring process and enable objective, diversity-oriented recruiting.

Another of our unique selling points is that we conduct candidate screening that is gamified and automated, with a structured interview, where the interview remains with the candidate’s profile. We roughly estimate that just for the 15 million open jobs on LinkedIn, if companies fill in 50% of those via external recruiting, and conduct a screening interview with 10 candidates per job filled at $50/hour paid to an employee to do the screening, that’s $3.75 billion and 75 million hours in direct costs. This is on top of applying for jobs, selecting CVs, and coordinating the process, which takes an even bigger financial and time toll on both applicants and recruiters. Instead, it would be better to take one interview for 1000 companies. The impact of what we want to achieve with our vision is enormous.

We also offer career discovery and career search tools for job candidates. This includes free, personalized feedback for every job-seeker. Right now, we’re aiming the service at students, bootcamp graduates and juniors, helping them to land jobs in tech and the creative industry at large. Next, we’ll expand into mid and senior roles. In the long run we want to reshape how recruiting happens through a common app that saves everyone in the market significant time and resources, helping people find jobs not only faster, but jobs that truly fit them.

Developing advanced AI applications with Google Cloud

We obtained our original funding from angel and institutional investors, and we were selected into the Fall 2021 batch of StartX, the non-profit start-up accelerator and founder community associated with Stanford University. But like most startups our budgets are tight, and we need to find ways to operate as efficiently as possible, especially when building out our technology stack and developer environment.

That’s where Google Cloud comes in. It’s a lot more affordable and flexible than competing solutions, and our developers love it. We use Google App Engine for the hosting and development of our applications giving us enormous flexibility. Vertex AI enables us to build, deploy, and scale machine learning models faster, within a unified artificial intelligence platform. On top of that we use Google Vertex AI Workbench as the development environment for the data science workflow, which allows us to have everything that we need to host and develop innovative AI-based applications.

BigQuery, Google Cloud’s serverless data warehouse, is another stand-out solution for us. We use it to crunch big data from all our systems and the UX is very intuitive and easy to use, allowing us to use it across the business and get insights from a wide range of employees, not just technical experts.

Above all, Google Cloud helps us solve the main platform challenges facing Gyfted including scalability and identity management, so we are perfectly positioned for growth. Right now, we handle about 2 million candidate interactions, a volume we expect to grow exponentially. As that number grows, we rely on Google Cloud to help us scale securely and with reliability.

Eliminating bias from the hiring process

Our technology partners have also been integral to helping us get to an advanced stage of our beta program. MongoDB on Google Cloud takes the data burden off our teams and reduces time to value of our applications. We can stay nimble and can scale database capacity at the push of a button.

Our collaboration with the Google team has been fantastic. Our Startup Success Manager is an expert when it comes to Google Cloud solutions, and he also understands our business from his own experience as an entrepreneur and an investor. It’s great to have an internal point of contact who can help us navigate all of Google’s resources.

I’d also stress the extent to which Google Cloud values align with ours. For example, a key benefit for our customers is the ability to strip unconscious bias out of the hiring process. Google Cloud tools support this commitment to diversity, especially when we are building out our AI models.

On a team level, we also appreciate the support that Google Cloud has shown through its Google Support Fund for Start-ups in Ukraine. This has helped many Ukrainian businesses to continue to operate at a very challenging time, including startups with remote, distributed teams in Poland where most of us stem from.

If I had to sum up Google Cloud and our collaboration with Google for Startups in a phrase, I’d say that it adds enormous value to our business while removing much of the risk when scaling up a start-up. We’ve seen the addition of many new tools and features in the past two years and our Google mentors are always looking at the best way these can be integrated with Gyfted’s own roadmap. That means that we can continue to transform recruiting and hiring processes with the support of one of the world’s most advanced tech companies as a strategic growth partner.

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