By Suhas Uliyar, Vice President, AI and Digital Assistant, Oracle
Call them chatbots, virtual assistants, or simply bots. Whatever the name, AI-powered conversational interfaces are becoming mainstream staples for consumers and enterprise alike.
In fact, leading analyst firm Gartner believes that “by 2022, 70 percent of white collar workers will interact with conversational platforms on a daily basis.” When Oracle unveiled its chatbot platform at OpenWorld 2016, it helped set the pace for automation in the enterprise. Automation is a means for increasing scale and efficiency and accelerating efforts to digital – and considering that recent global events and challenges have forced a restructuring of how we work, AI and digital assistants are fundamental to that transformation.
Oracle Digital Assistant has been solving the needs of the enterprise since 2016, and analyst firm Omdia recently noted, “By offering full integration with its software as a service (SaaS) applications, Oracle made it exponentially easier for end users to command and control the capabilities of these applications.”
Today we are announcing a new set of updates to enhance the multilingual capabilities of Oracle Digital Assistant. These features are helping customers such as Loyola University of Chicago and communications startup Yokeru provide their users with the information they need through the channel of their choice. The new features include:
New Deep Learning Models: Customers can leverage the power of Oracle Cloud Infrastructure’s native GPU and CPU architecture to improve the ability to distinguish nuances in customer queries, such as:
Similar vs. Unrelated phrases: “Can I get some flatbread?” vs. “Can I get some flowers?”
Additional context within long sentences: “I have a large party later this afternoon, and I have several guests coming over. I’d like to order some large pizzas.”
Closely related sentences: “I want to cancel my order” vs. “Why was my order cancelled?”
Distinguishing names that sound like locations: “When will Devon Arlington come to Stratford-Upon-Avon?” or “Find Paris Hilton from the Paris office”
Distinguishing number vs. currency: “Lunch with 3 for 60 bucks”
Colloquial terms: “I have a budget for 20M bucks” (colloquial usage)
Currency formats: “Please add a tip for 2,50 €” (different currency formats)
Versatile Data Shapes : Customers can use both large as well as small datasets to train their skills without concern that an imbalance would impact the NLU performance.
Custom Domain Vocabulary: Customers can expand the assistants understanding to their own custom domain vocabulary.
Data Manufacturing Pipeline: Data is critical to achieving high accuracy in deep learning models. The data manufacturing pipeline provides a cohesive set of tools providing all stakeholders, from technical to line-of-business, the ability to generate, refine, curate, and evaluate conversational data. Combining human sourced intelligence with advanced machine learning delivers better, more nuanced results that only humans can offer.
Native Multilingual: With Native Multilingual NLU, customers can add training data in different languages, eliminating the need for external translation services to understand users who do not speak English – and customers can provide multilingual outputs directly using resource bundles.
Key Phrase word clouds and Multilingual retrainer: Digital Assistant now features intent and key phrase clouds to help business analysts quickly understand common themes of engagements. The business analyst can quickly drill down into the details of a specific phrase.
Since its introduction, Oracle Digital Assistant has offered valuable features and capabilities, including:
Digital assistants for FAQs: When considering B2C call centers and B2E help desk, it’s easy to see how a bot can field common incoming questions and requests, providing customers the satisfaction of an instant response 24/7, while offloading staffing resources to work on other tasks.
Automated bot-to-agent transfer: Oracle Digital Assistant offers prebuilt integration to Oracle Service Cloud, offering a seamless experience for customers during handoff to a live agent, while providing agents historical information about the recent customer engagement.
Enterprise assistant skills: From cloud applications such as Oracle Cloud ERP, Oracle Cloud HCM, and Oracle Cloud CX to on-premises applications like PeopleSoft and JD Edwards, Oracle teams have developed prebuilt assistant skills and templates to meet customer demand.
Popular conversational channels: With support for well-known smart speakers to popular text-based channels including SMS, WhatsApp, WeChat, Facebook Messenger – plus collaboration tools like Slack and Teams – Oracle Digital Assistant is ready.
Oracle Voice : Oracle invested in its own AI-powered voice capabilities bringing together an end-to-end, secure, and private solution (GDPR, PII), while providing a customizable framework to support terminology that is unique to different industries and businesses.
One digital assistant: Oracle Digital Assistant can unify all assistant skills into one digital assistant, making it easy for users to interact with multiple systems from one conversation. Conversations are contextual and personalized to individual users and roles.
Chatbots and conversational AI are quickly becoming integral tools for enterprise communication and information sharing, in addition to automating traditionally manual tasks. With the new updates to Oracle Digital Assistant, we are delivering the innovative features users are seeking – such as multilingual capabilities – to further weave digital assistants into the fabric of the enterprise. As a result, customers are able to offer automation across their entire organization, using a highly secure AI-powered voice assistant that stores their business’ sensitive data in Oracle’s second generation cloud infrastructure.
