Jump to Content
AI & Machine Learning

Unlocking the power of AI with solutions designed for every enterprise

April 10, 2019
Levent Besik

Director of Product Management, Google Cloud Artificial Intelligence, Google Cloud

Many enterprises see the value in applying AI and machine learning to their business challenges, but not all have the necessary resources to do it. Where should your organization begin if you don’t already have a team of data scientists, or if your team is fully committed to other tasks? Businesses need a quick and easy way to bring AI to their organizations.

From the beginning, our goal has been to make AI accessible to as many businesses as possible. For example, last year we introduced Cloud AutoML to help businesses with limited ML expertise start building their own high-quality custom models. We also introduced BigQuery ML, which put the power of predictive analytics in reach of millions of users—even those without a data science background. And we’ve seen some amazing growth in demand for these services.

Today, we’re excited to announce a number of new solutions that provide an easy way to use AI to address common business challenges—such as analyzing documents, forecasting inventory and demand, or managing multiple customer service touchpoints such as chatbots, phone, and e-mail.

Here’s what’s new:

  • Document Understanding AI (beta)

  • Contact Center AI (beta)

  • Google Cloud for Retail:

    • Vision Product Search (GA)

    • Recommendations AI (beta)

    • AutoML Tables (beta)

Unlock insights from documents with Document Understanding AI—now in beta

Most companies have billions of documents—and moving that information into digital or cloud-native solutions where it can be easily accessed and analyzed can involve many hours of manual entry. These businesses need a way to automate this work as well as archive documents from multiple content sources into one cloud-based system.

Today we’re announcing Document Understanding AI, in beta, offering a scalable, serverless platform to automatically classify, extract, and enrich data within your scanned or digital documents. By turning your documents into structured data, Document Understanding AI can help automate document processing workflows. This means you can take advantage of the facts, insights, relationships and knowledge hidden in your unstructured documents and start making data-driven business decisions faster and more accurately. For instance, customers that use custom document classification have achieved up to 96% accuracy. Document Understanding AI easily integrates with technology stacks from partners and third parties—Iron Mountain, Box, DocuSign, Egnyte, Taulia, UiPath, and Accenture are already using it today.

"As the world's leading information management provider, Iron Mountain scans over 627 million pages every year as part of our digital transformation solutions. Google Cloud's Document Understanding AI helps us identify form fields, text passage, tables and graphs, as well as customer-specific keyword matching, for customized workloads,” says Jim O’Dorisio, Senior Vice President for Emerging Commercial Solutions, Iron Mountain. “Document Understanding AI provides a foundation to help us deliver a far more valuable set of services to our customers—assisting them in automated data understanding, enabling compliance, business value, and delivering peace of mind."

Improve customer care with Contact Center AI—now in beta

Last year we introduced our first AI solution, Contact Center AI to help businesses build modern, intuitive customer care experiences with the help of AI. Since then, Google Cloud customers have chosen to run substantial customer service workloads on Contact Center AI implementations built by partners like Cisco, Five9, Genesys, Mitel, Twilio, and Vonage.

Today, we’re announcing that Contact Center AI is now in beta. Contact Center AI builds on Dialogflow Enterprise Edition and provides key capabilities for your Contact Center—Virtual Agent, Agent Assist, and Topic Modeler—which are also available today in beta. The updates to our voice models, for example, make it easier for customers to have conversations with virtual agents. We’ve also made improvements to Agent Assist to quickly help surface useful content for live agents as they assist customers.

We're also thrilled to welcome new partners to the Contact Center AI program including 8x8, Avaya, Salesforce, and Accenture. Together, we'll integrate these partner services with Google's world-class speech recognition, synthesis, natural language understanding, and agent assist to improve the contact center experience.

Chris McGugan, Avaya’s Senior Vice President, Solutions and Technology explains, “We continue to expand our AI-enabled solutions as well as our cloud offerings for customers ranging from small-medium business to the largest global enterprises, and our ongoing collaboration with Google Cloud is providing additional capabilities to augment the innovation. By bringing these innovations to market for Avaya customers and partners, we enable them to make every customer interaction more meaningful and insightful, and more productive for their businesses. Avaya is also very encouraged by the enthusiastic response we have received from customers, analysts, and industry partners alike.”

Helping more retailers take advantage of AI

Whether they need to predict demand or provide automated product recommendations, retailers often have business challenges that can benefit greatly from AI. Google Cloud for Retail enables retailers to quickly take advantage of AI for retail-specific specific use cases.

And Vision Product Search, now generally available, makes it possible for retailers to build visual search functionality into their mobile apps, allowing customers to photograph an item and get a list of similar products from the retailer’s catalog. Recommendations AI, in beta, helps retailers provide personalized 1:1 recommendations to drive customer engagement and growth. It has generated up to 40 percent increases in recommendation-driven revenue and up to 5 percent increases in total revenue per session. Lastly, AutoML Tables, in beta, makes it possible for retailers to automatically build and deploy state-of-the-art machine learning models on structured data, reducing the total time required for modeling from weeks to days. This means they can easily leverage their enterprise data to predict outcomes that can help maximize their revenue, optimize their product portfolios, and better understand their customers.

To learn more, read our retail solutions blog post.

Continuing to bring AI to everyone

Today’s announcements build on our goal of making AI accessible to every business, wherever they may be in their AI journey. As applied machine learning serves more industries, our goal is to provide more packaged solutions as well as the best-in-class AI tools you need to deploy and customize solutions to suit your business or industry. To learn more about the full breadth of machine learning on Google Cloud, visit our website.

Posted in