Verve Group is an ecosystem of demand and supply technologies fusing data, media, and technology to deliver results and growth to both advertisers and publishers – no matter the screen or location, no matter who, what, or where a customer is. Classifying massive amounts of this unstructured data at scale is the first step in helping to surface relevant, high-quality content to users—and that’s where natural language processing (NLP) comes in.

Verve Group uses the NLP API from Google Cloud’s Vertex AI to fetch data for their internal content classification quality verification and as an additional source for building categorization models. By leveraging the NLP API’s Content Classification models, which are now generally available and offer Google’s latest large language model (LLM) technology, Verve Group powers classification through an updated and expanded training data set with over 1,000 labels and support for 11 languages (Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russia, Spanish, and Dutch join previously-available English). 

Verve Group has been using Google Cloud’s NLP API since day one, because of both the ease of implementation and the quality compared to competing NLP products. With documentation that is “comprehensive and self-explanatory,” the NLP API “allows for fast adoption and implementation, from test models all the way to production,” said Rami Alanko, GM of Verve Group.

Leveraging the NLP API has facilitated Verve Group’s fast go-to-market motions by enabling its customers to quickly discover and classify new content. “Operating on a global level with tens of different regions and languages, we have still been able to maintain high quality for our product and high retention rates with our clients,” Rami shared. “In a recent client case, we achieved 82% improvement in CTR when optimized with content quality measurements enabled by the API. In another client case, we drove brand safety risk down to 0.16% from 4% thanks to classification quality. Along with the new functionalities of the Google NLP, I can only see this trend continuing to strengthen.”

Verve Group is excited to further expand their NLP use cases by leveraging the new Content Classification models, which have already helped them expand their classification inventory, improve the quality and performance of their quality verification for customers, and unlock new use cases for NLP. “Our classification model accuracy improved 41% using Google NLP as a verification partner,” said Rami.  

Additionally, Verve Group is now using the API for metadata analysis on a  large image database. “We browse the database and run the image metadata via our classification. This flow enables us to classify images reliably aligned with our standard classification.  We pretty much use the same data flow for our runtime in-app textual content analysis, therefore allowing for close to real-time consumer engagement,” Rami added.

To learn more about how companies are leveraging NLP API from Google Cloud Vertex AI, click here, and to learn more about Google Cloud’s work with foundation models and generative AI, read The Prompt on Transform with Google Cloud.

How will your organization manage this year’s data growth and business requirements? Your actions and strategies involving data and AI will improve or undermine your organization’s competitiveness in the months and years to come. Our teams at Google Cloud have an eye on the future as we evolve our strategies to protect technology choice, simplify data integration, increase AI adoption, deliver needed information on demand, and meet security requirements. 

Google Cloud worked with* IDC on multiple studies involving global organizations across industries in order to explore how data leaders are successfully addressing key data and AI challenges. We compiled the results in our 2023 Data and AI Trends report. In it, you’ll find the metrics-rich research behind the top five data and AI trends, along with tips and customer examples for incorporating them into your plans. 

1: Show data silos the door

Given the increasing volumes of data we’re all managing, it’s no surprise that siloed transactional databases and warehousing strategies can’t meet modern demands. Organizations want to improve how they store, manage, analyze, and govern all their data, while reducing costs. They also want to eliminate conflicting insights from replicated data and empower everyone with fresh data.

A unified data cloud enables the integration of data and insights into transformative digital experiences and better decision making.

Andi Gutmans, GM and VP of Engineering for Databases, Google Cloud

Tweet this quote

In the report, you can learn how to adopt a unified data cloud that supports every stage of the data lifecycle so that you can improve data usage, accessibility, and governance. Inform your strategy by drawing on organizations’ examples such as a data fabric that improves customer experiences by connecting more than 80 data silos, as well as other unified data clouds that save money and simplify growth. 

2: Usher in the age of the open data ecosystem

Data is the key to unlocking AI, speeding up development cycles, and increasing ROI. To protect against data and technology lock-in, more organizations are adopting open source software and open APIs.

Tweet this quote

Understand how you can simplify data integration, facilitate multicloud analytics, and use the technologies you want with an open data ecosystem, as described in the report. Learn from metrics about global open source adoption and public dataset usage. And explore how global companies adopted open data ecosystems to improve patient outcomes, increase website traffic by 25%, and cut operating costs by 90%.

3: Embrace the AI tipping point

Pulling useful information out of data is easier with AI and ML. Not only can you identify patterns and answer questions faster but the technologies also make it easier to solve problems at scale.

We’ve reached the AI tipping point. Whether people realize it or not, we’re already using applications powered by AI—every day. Social media platforms, voice assistants, and driving services are easy examples.

June Yang, VP, Cloud AI and Industry Solutions, Google Cloud

Tweet this quote

Organizations share how they’re reaching their goals using AI and ML by empowering “citizen data scientists” and having them focus on small wins first. Gain tips from Yang and other experts for developing your AI strategy. And read how organizations achieve outcomes such as a reduction of 7,400 tons per year in carbon emissions and a more than 200% increase in ROI from ad spend by using pattern recognition and other AI capabilities. 

4: Infuse insights everywhere

Yesterday’s BI solutions have led to outdated insights and user fatigue with the status quo, based on generic metrics and old information. Research shows that as new tools come online, expectations for BI are changing, with companies revising their strategies to improve decision making, speed up the development of new revenue streams, and increase customer acquisition and retention by providing individuals with needed information on demand.

Organizations are equipping business decision-makers with the tools they need to incorporate required insights into their everyday workflows.

Kate Wright, Senior Director, Product Management, Google Cloud

Tweet this quote

In the report, you’ll discover why and how data leaders are rethinking their BI analytics strategies and applications to improve users’ trust and use of data in automated workflows, customizable dashboards, and on-demand reports. Global companies also share how they improve decision making with self-service BI, customer experiences with IoT analysis, and threat mitigation with embedded analytics.

5: Get to know your unknown data

Increasing data volumes can make it harder to know where and what data they store, which may create risk. Case in point: If a customer unexpectedly shares personally identifiable information during a recorded customer support call or chat session, that data might require specialized governance, which the standardized storage process may not provide.

If you don’t know what data you have, you cannot know that it’s accurately secured. You also don’t know what security risks you are incurring, or what security measures you need to take.

Anton Chuvakin, Senior Staff Security Consultant, Google Cloud

Tweet this quote

Check out the report to learn about data security risks that are often overlooked and how to develop proactive governance strategies for your sensitive data. You can also read how global organizations have increased customer trust and productivity by improving how they discover, classify, and manage their structured and unstructured data.  

Be ready for what’s next

What’s exciting about these trends is that they’re enabling organizations across industries to realize very different goals using their choice of technologies. And although all the trends depend on each other, research shows you can realize measurable benefits whether you adopt one or all five.

Review the report yourself and learn how you can refine your organization’s data and AI strategies by drawing on the collective insights, experiences, and successes of more than 800 global organizations. 

From the historic Gold Country to the rugged heights of the Sierra Nevada, Placer County encompasses more than 1,500 square miles—and provides services to nearly 400,000 residents. Across the county, residents access resources in person, over the phone, and through the county website. In 2018, the county piloted a suite of eServices through its Community Development Resource Agency (CDRA) with the goal of helping its geographically dispersed population more easily apply for permits, make appointments, and get immediate answers to specific questions.

Now, with the help of Google Cloud Dialogflow and Speech-to-Text API, the county has created a virtual agent that enables anyone, anywhere, to simply start a conversation by saying “Ask Placer County” into a variety of voice assistant hardware. This virtual agent builds on the success of eServices and helps the public access information through their smartphones or smart home devices, which is especially helpful for individuals without immediate access to a computer—such as the traveling public or a contractor working on-site, for example.

The pilot program has been an opportunity to explore new technology and create another communication channel to our citizens. “Our ambitious and long-term goal is that ‘Ask Placer County’ will be like having a personal assistant to everything related to Placer County. While the virtual agent is currently limited to a few departments, we plan to expand it countywide,” says Ben Palacio, senior IT analyst for Placer County.

“Our ambitious and long-term goal is that ‘Ask Placer County’ will be like having a personal assistant to everything related to Placer County. While the virtual agent is currently limited to a few departments, we plan to expand it countywide.”

—Ben Palacio, Senior IT Analyst, Placer County

New eServices get a boost from AI virtual agent

The CDRA, one of many departments and agencies within Placer County, deployed interactive eServices for residents. As part of this initiative, the CDRA made a special request to the information technology (IT) department: Build an AI-based virtual agent that would spotlight the eServices on the website and make them easily available through a conversational interface.

“Having a specific technology requirement voiced by an agency was visionary and very welcome. It meant they were engaged and excited about the possibilities that these new technologies had to offer,” says Mike Spak, IT Manager for Placer County.

Today, the CDRA’s eServices help residents answer important questions, such as: “Is my land zoned for adding a garage?” “What historical engineering work has been done on my property?” And, “How can I make an appointment at a permitting office?”

“Having a specific technology requirement voiced by an agency was visionary and very welcome. It meant they were engaged and excited about the possibilities that these new technologies had to offer.”

—Mike Spak, IT Manager, Placer County

Google Cloud fit easily into Placer County’s multivendor environment

With the help of consultants from Dito, a Google Cloud Premier Partner, Placer County chose Google Cloud to help with “Ask Placer County.”

Placer County runs a multivendor IT environment. “Especially with the cloud, the easier it is to integrate a vendor’s capabilities with others, the better for everybody,” says Palacio. “Google Cloud was able to integrate with other vendors’ capabilities for this project.”

For example, Placer County uses the Google Cloud operations suite (formerly Stackdriver) to monitor, troubleshoot, and improve its cloud infrastructure and application performance. And it uses Dialogflow, which powers the natural language processing (NLP) interface of the “Ask Placer County” virtual agent. Both integrate easily with tools from other vendors.

“Especially with the cloud, the easier it is to integrate a vendor’s capabilities with others, the better for everybody. Google Cloud was able to integrate with other vendors’ capabilities for this project.”

—Ben Palacio, Senior IT Analyst, Placer County

Real-time conversations powered by “Ask Placer County”

Dito got “Ask Placer County” up and running using App Engine and Datastore. Today, the “Ask Placer County” virtual agent provides information ranging from how to adopt a pet to short-term-rental compliance.

Users can say “Ask Placer County” into their smartphones or their computer microphones and access targeted information from the pilot departments. IT staff reviews the asked questions and are constantly updating the virtual agent to provide more accurate and responsive information.

“You could be in your backyard with a contractor trying to get a project started, and if the contractor has a question about permitting or zoning, they can use their smartphone to get an answer right then and there, rather than having to interrupt the meeting, get back in their car, and drive to a county office,” says Palacio.

The county hopes “Ask Placer County” will improve the efficiency of in-person interactions between the public and county employees as well. Because the public can access common questions and information online or through the virtual agent, employees’ interactions with the public can be more focused and productive.

“We are providing more effective and efficient service to our customers through 24/7 access to information and by reducing the proportion of staff’s time in responding to emails and voicemails to answer our customer questions,” says Shawna Purvines, Principal Planner for Placer County.

According to Placer County, the virtual agent currently answers a monthly average of around 200 questions for the CDRA, and the county continues to develop more and more complete answers across participating departments.

“We are providing more effective and efficient service to our customers through 24/7 access to information and by reducing the proportion of staff’s time in responding to emails and voicemails to answer our customer questions.”

—Shawna Purvines, Principal Planner, Placer County

Constantly evolving based on users’ needs

To best serve the needs of the CDRA, and potentially other departments over time, “Ask Placer County” continues to evolve. The county can add and retire questions based on the needs of constituents. This technology can be tailored to address current needs, such as responding to COVID-19. “Our hope is that, in quickly evolving situations, the virtual agent can be a resource for the public to access real-time information about public services,” says Palacio.

As a component of the eServices group, “Ask Placer County” has kept construction and development in Placer County operational during the COVID-19 pandemic, and it continues to provide opportunities for the public to access county resources without coming in to the counters, reducing the need for in-person visits. In fact, according to Placer County data, permit applications have increased by 17%.

Placer County also performs analytics using the Google Cloud operations suite to gain insights into the most popular questions and, just as importantly, the questions that are not being answered. “We get insight into what we’re missing—for those times when the virtual agent can’t find a response in our database,” says Palacio. Placer County uses these insights to improve answers and ultimately improve the efficacy of the virtual agent over time.

“This continual, real-time learning is the exciting part of the application that lets us help constituents in entirely new ways. It’s really cool,” says Palacio.

County IT workers actively analyze CDRA webpages to determine which are the most visited and to craft questions and answers to add to “Ask Placer County.” According to Placer County, the number of questions the virtual agent can answer is now more than 600. But the CDRA pages are just a small subset of the 5,000 pages that make up the Placer County website. A future goal is to provide a backstop for customer questions that can’t be answered, transferring those customers to county staff for resolution.

“Looking ahead, this technology has the ability to provide answers to thousands and thousands of questions,” says Palacio.

“This continual, real-time learning is the exciting part of the application that lets us help constituents in entirely new ways. It’s really cool.”

—Ben Palacio, Senior IT Analyst, Placer County

Scaling “Ask Placer County” countywide

The limited rollout of the virtual agent technology allowed IT to monitor its effectiveness and make initial adjustments. As the virtual agent evolves, the Placer County chief information officer sees opportunities for it to engage the public countywide.

The “Ask Placer County” virtual agent can truly be a concierge, helping the public navigate county resources. It can help citizens become more engaged with their elected officials, it can provide information, and it can more efficiently connect the public with the services they seek.

Some of the future possibilities include providing current information on board meetings and individual elected officials, checking on permit status and burn days, and getting the latest county news. “There are so many ways we can use this solution to tackle issues within the county that we’re going to have to somehow prioritize them,” says Palacio.

As data environments become more complex, companies are turning to streaming analytics solutions that analyze data as it’s ingested and deliver immediate, high-value insights into what is happening now. These insights enable decision makers to act in real time to take advantage of opportunities or respond to issues as they occur.

While understanding what is happening now has great business value, forward-thinking companies are taking things a step further, using real-time analytics integrated with artificial intelligence (AI) and business intelligence (BI) to answer the question, “what might happen in the future?” Arkansas-based Tyson Foods has embraced AI/BI analytics to enable predictive insights that unlock new opportunities and drive future growth.

Creating a digital twin for connected intelligence company wide

Before using AI/BI, Tyson’s analytics capabilities consisted of traditional BI solutions focused on KPIs and simplifying data so that humans could understand it. Tyson wanted to leverage its data to uncover ways to improve current processes and grow its business. But with BI alone, Tyson struggled to use data to run the simulations and scenarios essential to make educated decisions. To keep growing, it had to embrace the complexity of its data, building ways to analyze it and use it to inform decision making. 

Tyson’s on-premises analytics solutions limited its ability to be aggressive and make intelligent, timely, prescriptive decisions. The solution was to create a digital twin to scale optimizations within business processes, moving from local optimizations to system-wide connected optimizations. Doing so meant shifting entirely to cloud computing, with an initial focus on building the ingestion component of the digital twin platform.

Investing in a digital twin enabled Tyson to accelerate new capabilities like supply chain simulation “what-if” scenarios, prescriptive price elasticity recommendations, and improvement of customer intimacy. 

Solving the ingestion problem for faster time to insights

Before its migration to Google Cloud, analytics projects that Tyson suffered from uncertainty over how to obtain the data. This problem was prolific and caused project times to be extended for weeks or even months due to the need to write and support one-off data ingestion processes at the front end. This problem also prevented the IT team from delivering analytics solutions fast enough for the business to take full advantage of them. 

To solve this analytics problem, the team created Data Ingestion Compute Engine (DICE). DICE is a Google Cloud-hosted, open-source, cloud-native ingestion platform developed to provide configuration-based, no-ops, code-free ingestion from disparate enterprise data systems, both internal and external. It is centered on three high-level goals:

1. Accelerate the speed of delivery of IT analytics solutions
2. Enable growth of IT capabilities to produce meaningful insight
3. Reduce long-term total cost of ownership for ingestion solutions

Creating DICE ingestion platform with Google Cloud services

Teams use DICE to set up secure data ingestion jobs in minutes without having to manage complex connections or write, deploy, and support their own code. DICE enables unbound scale, highly parallel processing, DevSecOps, open source, and the implementation of Lambda Data Architecture.

A DICE job is the logical unit of work in the DICE platform, consisting of immutable and mutable configurations persisted as JSON documents stored in Firestore. The job exists as an instruction set for the DICE data engine, which is Apache Beam running Dataflow to instruct which data to pull, how to pull it, how often to pull it, how to process it, when it changes, and where to direct it.

Two of DICE’s primary layers include the metadata engine and the data engine. The metadata engine is responsible for the creation and management of DICE job configuration and orchestration. It is made up of many microservices that interact with multiple Google Cloud services, including the job configuration creation API, job build configuration helper API, and job execution scheduler API.

The data engine is responsible for the physical ingestion of data, the change detection processing of that data, and the delivery of that data to specified targets. The data engine is Java code that uses the Apache Beam unified programming model and runs in Dataflow. It is comprised of streaming, jobs, and Dataflow flex template batch jobs. Logically, the data engine is segmented across three layers: the inbound processing layer, the DICE file system layer, and the target processing layer, which takes the data from the DICE file system and moves it to targets.

Rolling DICE for thousands of ingestion jobs each day

DICE was first deployed to a production environment in November 2019, and just two years later, it has more than 3,000 data ingestion jobs from more than a hundred disparate data systems, both internal and external to Tyson Foods. Most of these jobs run multiple times a day. On a daily basis the DICE environment sees more than 25,000 Dataflow jobs running and an average of 3.25 terabytes of new data being ingested.

DICE supports ingestion from many different types of technologies, including BigQuery, SQL Server, SAP HANA, Postgres, Oracle, MySQL, Db2, various types of file systems, and FTP servers. Additionally, DICE supports target platform technologies for ingestion jobs that include multiple JDBC targets, multiple file system targets, and BigQuery and queue-based store and forward technologies. 

The platform continues to see linear growth of DICE jobs, all while keeping platform costs relatively flat. With increasing demand for the platform, Tyson’s IT team is constantly enhancing DICE to support new sources and targets.

This intelligent platform keeps adding new value and makes it simple for Tyson to take advantage of its data. This innovation is a necessity in this fast-changing world of digital business in which companies must transform a high volume of complex data into actionable insight.

If you’ve ever used only your voice to authenticate a payment, place an order, or check an account over the phone, there is a good chance that Pindrop’s technology made it possible.

Founded in Atlanta in 2011, Pindrop provides software and technology that uses machine learning, voice recognition, and behavioral analytics to help detect and prevent fraud in voice channels like AI-powered call centers and solve the long standing identity problem commonly encountered in customer care and contact center experiences. Demand for Pindrop’s technology has grown considerably over the past decade, as more organizations and people adopt voice as an interface for customer service, transactions, entertainment and more. As that demand has grown, safeguarding these voice interactions from fraud or authentication loops continues to be a unique challenge.

Now, with frictionless voice-driven customer experiences at an all-time high, cybersecurity is more critical than ever. In fact, research shows that fraudsters are able to accurately answer knowledge-based authentication questions 92% of the time, as opposed to only 46% for actual customers. To address this, Pindrop is bringing its products and technology to Google Cloud in order to scale and develop new capabilities that will help enable the next wave of voice-first interfaces and call centers.

The new partnership will enable Pindrop’s teams to accelerate their development of new capabilities to address an ever-shifting landscape – like detecting deep fakes and robocalls, helping banks authenticate transactions, providing retailers with AI-powered call center support, and helping IoT makers optimize for security, speed and simplicity.

More specifically, the partnership will help Pindrop scale its own businesses, and meet ever-growing customer needs in several ways.

First, Pindrop is bringing its SaaS platform to Google Cloud, enabling customers to deploy it at global scale, on secure, sustainable, and highly performant cloud infrastructure. Not only does this give Pindrop the ability to deliver secure voice interactions with low-latency, it also aligns with its mission to enable customer choice when selecting and implementing security technology. And for customers already operating on Google Cloud, getting started with Pindrop can be done directly within their cloud environment, now that the company is making its solutions available on Google Cloud Marketplace.

Second, Pindrop plans to offer its voice secure technology with Google Cloud’s Contact Center AI (CCAI) capabilities to develop new solutions that will enhance call center experiences. CCAI capabilities in understanding, augmenting, and ML-processing conversations allows companies to deliver interactions that are helpful and keep costs low. These capabilities alongside Pindrop’s authentication and anti-fraud solutions will enable the company with the tools and technologies needed to create the next evolution of frictionless experiences in a secure way.

Finally, building on top of Google Cloud will equip Pindrop with multicloud capabilities that will offer new channels to increase revenues through. Using technologies like Google Kubernetes Engine, frequently chosen by startups and tech companies, to quickly launch and scale new ML applications up or down will also support Pindrop’s growth as it adds to its suite of technologies.

Supporting innovative startups and digital native businesses like Pindrop is in Google’s DNA, and we’re delighted to support Pindrops’ growth, and the success of their customers, with Google Cloud infrastructure, Contact Center AI, and go to market expertise.

You can learn more about Pindrop on Google Cloud here, and Google Cloud’s Contact Center AI solution here.