Despite a growing number of diversity, equity, and inclusion (DEI) initiatives, Black and Latinx people remain highly underrepresented in tech. Although comprising 12.6% and 18% of the U.S. labor force respectively, Black professionals hold only 5% of tech positions, while Latinx professionals fill just 6% of tech roles.

Long-standing biases in hiring practices and non-inclusive work environments are the primary contributors to this lack of diversity. Even when underrepresented professionals are successfully recruited, invisible barriers to promotion and layoffs that disproportionally impact Black and Latinx employees make it extremely challenging for tech firms to retain top talent.

We founded Divercity to help employers build diverse workforces that are more inclusive and sustainable. With our comprehensive recruiting and retention platform, tech companies can accurately measure employee diversity and gender parity, seamlessly connect with underrepresented talent, and significantly reduce turnover.

As Divercity continues to grow, we’ll introduce new services and solutions that empower the tech world to build inclusive companies while improving compliance with state and federal equal opportunity laws. We also hope to expand the reach of Divercity to support DEI initiatives in non-tech industries and bolster recruiting underrepresented professionals in other countries as well.

Scaling Divercity with the help of the Google for Startups Black Founders Fund

Shortly after founding Divercity, we participated in the 2021 Techstars Workforce Development Accelerator. The incredible support and guidance we received during and after the program highlighted the importance of long-term collaboration with reliable technology partners who actively champion diversity and inclusion.

That’s why we became part of the Google for Startups Cloud Program. After completing the program, we used Google Cloud credits and Google for Startups Black Founders Fund funding to cost-effectively trial, deploy, and scale key Google Cloud solutions. In just months, we rolled out new inclusion tracking and recruiting tools on the highly secure-by-design infrastructure of Google Cloud to expedite the sourcing and hiring of underrepresented talent in the tech industry.

With the support and mentorship of the Google for Startups Cloud Program and the Black Founders Fund, Divercity is well on its way to becoming one of the industry’s most trusted sites for DEI measurement, recruitment, and retention.

Delivering predictive diversity analyses with a 99% accuracy rate

We rely on the expansive Google Cloud ecosystem to power all the services offered on the Divercity platform. Specifically, we leverage Colab to write and execute the sophisticated TensorFlow machine learning (ML) models that deliver our predictive diversity analyses with a 99% accuracy rate.

We also use BigQuery to democratize insights and run analytics at scale with 27% lower three-year TCO than cloud data warehouse alternatives. BigQuery seamlessly integrates with Looker and Data Studio to display company diversity and recruitment data on interactive dashboards—and automatically populate reports with detailed demographic information.

We also accelerate the development, launch, and management of new Divercity tools with Firebase, while taking advantage of key features such as A/B testing and messaging campaigns to boost user engagement.

In the future, we plan to explore how Google Cloud AI and machine learning products such as Vertex AI and AutoML can further refine our diversity score analyses and applicant recruiting pipeline. We’ll also continue leveraging the many resources provided by the Google Black Founders Fund, including opportunities for technical project partnerships, early access to new Google Cloud products and tools, and collaboration with dedicated Google experts.

The Google for Startups Cloud Program and Google Black Founders Fund have been invaluable to our success. Since completing the Black Founders Accelerator program, we’ve been named a top 10 HR tech product by HR Tech Outlook, significantly increased our subscriber base, and received positive feedback from investors. We can’t wait to see what we accomplish next as we empower tech companies to build more diverse, inclusive, and sustainable workforces.

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.

Organizations are pressed with the need to engage, retain, and upskill employees with many positions staying fully or partially remote as the pandemic continues. The Center for Digital Government (CDG) reports that 74% of state and local governments believe they will continue hybrid operations for the long-term. This transition is the latest in a long list of reasons agencies are looking for solutions to help train their workforce digitally. Some have found Google Classroom to be the perfect solution.

The State of Iowa knew about the advantages of digital classrooms even before the pandemic. They were already successfully using Google Classroom for in-person training, making the transition to digital seamless when the state closed down. Jessica Van Heuveln, a Google support specialist for the State of Iowa CIO’s Office, says the switch to digital doesn’t deprive workers of hands-on training. “You can use Google Classroom for many different environments, so if you’re doing self-taught, in-person or virtual training, it’s going to work with all those approaches.”

The logistics of a digital classroom

Iowa uses Google Classroom to onboard and upskill employees as well as train volunteers. When the pandemic shifted the state’s workforce to 70% working from home, they needed a  platform that could not only handle a vast range of topics and teaching styles to support remote workers but also scale to meet their demand. Van Heuveln notes that Google Classroom was particularly helpful for handling compliance training, especially with its integration with Google Meet. These trainings often require an entire sector of the workforce to attend a single class with more than 100 attendees, according to Van Heuveln. The logistics of these larger sessions cuts down on the number of total sessions the state needs to host. Iowa also found that employees were less apprehensive about learning when they could do it from the comfort of their own homes.

Iowa follows a train-the-trainer model to train employees expected to instruct using Google Classroom. Trainers working in departments across the state learn to use Google Classroom to create and host virtual learning experiences specific to their own departments. 

Collaborative classrooms made simple

Google Classroom meets many needs for Iowa, such as setting up training, managing attendance, reviewing uploaded coursework, and communicating with attendees. Both course attendees and trainers have everything they need in one place, and robust engagement tools help attendees stay focused while giving trainers the feedback they need from their lessons. Built-in survey options let trainers gauge attendee knowledge, and the chat function ensures no one ever misses a question. The reporting dashboard gives trainers access to analytics to track engagement and attendance, providing insights that can improve future training sessions.

Google Classroom also makes it easier to ensure attendees stay on board throughout the training program. Coursework can be uploaded directly into Google Classroom, and training sessions can be recorded and archived. This feature allows employees to work at their own pace or lets them catch up when a scheduling conflict means they might miss a session.

The enterprise version of Google Classroom Iowa uses interfaces with other Google Workspace tools such as Google Meet, Google Calendar, Google Drive, and Gmail, which streamlines training and leads to more collaboration between employees and trainers. It can also interface with applications from other providers, further boosting its utility as an effective virtual classroom. Google Drive stores training materials securely. Lastly, Google Classroom enterprise comes with 24/7 support to make sure agencies always have everything they need for success.

Helping employees be better prepared to serve

Google Classroom can be a powerful part of any training program, whether it be digital or in-person. Building virtual connections empowers organizations to deliver better experiences. Google Classroom is helping the State of Iowa accomplish this for their constituents. Designed to scale and be accessible from anywhere, the platform helps public employees better serve the public. Virtual training strategies are essential for agencies that are looking to grow their workforce and build employee skill levels. The most important thing, however, is that training programs enable employees to further your agency’s mission. To learn more about Google Classroom and see more solutions designed with government in mind, check out the Google Cloud for government page.

From data centers and cloud regions to subsea cables, Google is committed to connecting the world. Our investments in infrastructure aim to further improve our network—one of the world’s largest—which helps improve global connectivity, supporting  users and Google Cloud customers. Our subsea cables play a starring role in this work, linking up cloud infrastructure that includes more than 100 network edge locations and over 7,500 edge caching nodes. 

As it turns out, readers of this blog seem to find what happens under the sea just as fascinating as what’s going on in the cloud. Posts on our cables are consistently among our most popular, which is why we brought them together for you here so you can take a deeper dive (pun intended).

Here’s a list our most popular posts on our underwater infrastructure:

2021

• Hola, South America! Announcing the Firmina subsea cable
• This bears repeating: Introducing the Echo subsea cable
• The Dunant subsea cable, connecting the US and mainland Europe, is ready for service

2020

• Announcing the Grace Hopper subsea cable, linking the U.S., U.K. and Spain

2019

• Introducing Equiano, a subsea cable from Portugal to South Africa
• A quick hop across the pond: Supercharging the Dunant subsea cable with SDM technology
• Curie subsea cable set to transmit to Chile, with a pit stop to Panama

2018

• Expanding our cloud network for a faster, more reliable experience between Australia and Southeast Asia
• Delivering increased connectivity with our first private trans-Atlantic subsea cable

2017

• Google invests in INDIGO undersea cable to improve cloud infrastructure in Southeast Asia

2016

• New undersea cable expands capacity for Google APAC customers and users
• Google Cloud customers run at the speed of light with new FASTER undersea pipe
• A journey to the bottom of the internet

Our cable systems provide the speed, capacity and reliability Google is known for worldwide, and at Google Cloud, our customers can make use of the same network infrastructure that powers Google’s own services. To learn more, you can view our network on a map, or read more about our network.

The home lending journey entails processing an immense number of documents daily from hundreds of thousands of borrowers. Currently, home lending document processing relies on some outdated digital models and a high dependency on manual labor, resulting in slow processing times and higher origination costs. Scaling a business that sorts through millions of documents daily, while increasing efficacy and accuracy, is no small feat. When it comes to applying for a mortgage loan, consumers expect a digital experience that’s as good as the in-person one. Roostify simplifies the home lending journey for lenders and their customers.

No time to spare: Overcoming document processing challenges with AI

Roostify provides enterprise cloud applications for mortgage and home lenders. In order to empower its customers to deliver a better, more personalized lending experience, they needed to automate and scale their in-house document parsing functionality.

As a key component of its document intelligence service, Roostify is leveraging Google Cloud’s Lending DocAI machine learning platform to automate processing documents required during a home loan application process, such as tax returns or bank statements with multi-language support. This partnership delivers data capture at scale, enabling Roostify customers to automatically identify document types from the uploaded file and to extract relevant entities such as wages, tax liabilities, names, and ID numbers for further processing, and make things move faster in the cumbersome lending process. 

Roostify’s solutions leverage Google Cloud’s Lending DocAI, which is built on the recently announced Document AI platform, a unified console for document processing. Customers can easily create and customize all the specialized parsers (e.g., mortgage lending documents and tax returns parsers) on the platform without the need to perform additional data mapping or training. All Google Cloud’s specialized parsers are fine-tuned to achieve industry-leading accuracy, helping customers and partners confidently unlock insights from documents with machine learning. Learn more about the solution from the GA launch blog and the overview video.

Integrating Lending DocAI’s intelligent document processing capabilities into the Roostify platform means more innovation for their customers and tangible results: faster loan processing times, fewer document intake errors, and lower origination costs. Additional support in Google Lending DAI for other languages and more documents like global Know Your Customer (KYC) documents or payroll reports is in the near future.

Full integration of AI solutions

Working together with Roostify’s platform team, we were able to help them solve their document processing challenge through integration of various GCP products such as Lending DocAI (LDAI), Data Loss Prevention (DLP) for redacting sensitive data, BigQuery for data warehousing and analytics, and Firestore for API status. To make it very safe and secure, all data was encrypted end-to-end at Rest and in Transit. LDAI won’t require any training data to process. It is an easy plug and play API.

Here is a sneak peek in the high level deployment architecture for LDAI in Roostify environment:

Here are the steps for processing data:

1. Receives document processing request from the client.
2. API Function directs requests to the pre-processing service. For Async requests a processing ID is generated and returned to the caller.
3. Pre-processing service sends the request for further processing (Long/short PDF conversion), calling other microservices and receives back the responses. Any error in the response received is then sent to the response processing service. 
4. If the response is synchronous, the pre-processing service directs it to the LDAI Invoker service. 
   1. If the response is asynchronous, the pre-processing service feeds it into the Cloud Pub/Sub service.
5. Cloud Pub/Sub service feeds the response back to the LDAI Invoker service.
6. LDAI Invoker service routes the request to the Google LDAI API for classification if there are multiple pages in the document.
7. Document will be split based on LDAI response and then saved in a GCS bucket for temporary storage.
8. LDAI entity interface for single page processing and then LDAI Invoker sends LDAI results to LDAI Response Processing
9. If a request is a synchronous request the LDAI Response Processor sends results to the API Function so that it can complete the synchronous call and respond to the rConnect caller.
   1. If the request is an asynchronous request the LDAI Response Processor will respond to the caller’s webhook and complete the transaction.
10. Finally, Data stored in the GCP bucket will be deleted.

All the responses that come from the LDAI API can optionally feed into BigQuery via the Response Processor, after parsing it through Data Loss Prevention (DLP) API to redact the PII/sensitive information.  Throughout the processing of both asynchronous and synchronous requests all transactions are logged using Cloud Logging.  For asynchronous transactions, the state is maintained throughout the process using Cloud Firestore.

Roostify currently uses this technology to power two different solutions: Roostify Document Intelligence and Roostify Beyond™. Roostify Document Intelligence is a real-time document capture, classification, and data extraction solution built for home lenders. It ingests documents uploaded by borrowers and loan officers, identifies the relevant documents, and extracts and classifies key information. Roostify Document Intelligence is available as a standalone API service to any home lender with any digital lending infrastructure already in place. 

Roostify Beyond™ is a robust suite of AI-powered solutions that enables home lenders to create intelligent experiences from start to close. It combines powerful data, insightful analytics, and meaningful visualization to streamline the underwriting process. Roostify Beyond™ is currently available only to Roostify customers as part of an Early Adopter program and will be rolled out to the market later this year.

Through this partnership, Roostify has enabled its customers to adopt a data-first approach to their home lending processes, which will lead to improved user experiences and significantly reduced loan processing times.

Fast track end-to-end deployment with Google Cloud AI Services (AIS)

Google AIS (Professional Services Organization), in collaboration with our partner Quantiphi, helped Roostify deploy this system into production and fast-tracked the development multifold to generate the final business value.

The partnership between Google Cloud and Roostify is just one of the latest examples of how we’re providing AI-powered solutions to solve business problems.