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Google supercharges enterprise contact centers with Gemini 1.5 Flash

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Google supercharges enterprise contact centers with Gemini 1.5 Flash

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Today, Google Cloud announced it is rebranding its six-year-old Contact Center AI offering as a new end-to-end application called Customer Engagement Suite with Google AI.

The move, which is another significant product rebrand from Google, has been made to reflect the integration of the company’s generative AI technologies – including the all-new Gemini 1.5 Flash – into the platform and provide enterprises with a more powerful experience for handling customer cases across different touchpoints.

This means enterprises using the application will now get advanced generative AI capabilities, including agentic AI to handle customer queries as well as smart replies, summaries and more to make customer care representatives more efficient at handling complex cases.

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What does the new end-to-end application have on offer?

Google Cloud launched Contact Center AI in 2018 as a multichannel platform that integrated with CRMs and other data sources and provided customer care reps the ability to handle cases across different channels (across web, mobile, voice, email, apps). The offering included early-level AI and machine learning (ML) capabilities, including recommended responses (like those seen in Gboard), DialogFlow-based virtual agents for basic queries and transcription analysis for live insights and optimization.

Now, with this rebrand, Google Cloud is building on this work and adding features powered by its foundation models — while keeping the same omnichannel communication experience.

Firstly, the conversational agents offering of the platform, which created basic virtual agents, can now create more advanced hybrid agents, integrating prescriptive actions for predetermined questions as well as Gemini’s ability to address a broader range of topics. This way, a company can address customer questions with the best of both worlds — rule-based deterministic control and adaptive generative AI, grounded in the organization’s proprietary datasets.

“You can create and control virtual agent behavior with no code, making the product easy to use and configure for a wider range of employees. The hybrid virtual agents you create can reduce costs across customer operations by taking on a greater volume of inquiries to increase customer self-service and allow customer-care representatives to focus on more specialized calls,” Duncan Lennox, VP & GM of Applied AI at Google Cloud, wrote in a blog post.

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In addition to improved virtual agents, Google Cloud has enhanced the Agent Assist offering to provide customer care reps with more Gemini-powered tools to address queries faster and with high levels of accuracy. 

This includes generative knowledge assist to suggest search queries based on the context of the ongoing conversation; a coaching model that can be grounded in proprietary information to generate real-time step-by-step guidance for representatives; and enhanced smart replies, automatic call summarization and live bi-directional translation for chats, covering over 100 languages. 

Notably Agent Assist will also tap Gemini 1.5 Flash’s multimodal capabilities to help agents instantly generate media to handle customer queries. This can come particularly handy in cases of tech support, where the agent has to give step-by-step instructions to the customer.

By enhancing Contact Center AI with Gemini smarts, Google Cloud hopes enterprises will be able to orchestrate a consistent customer experience and better address queries across all touchpoints. The company currently supports customer service agents of dozens of large enterprises, including Verizon, Marks & Spencer, EasyJet, Telus and the State of Illinois

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However, it is worth noting that the Sundar Pichai-led company is not the only one exploring the power of AI in the contact center. Multiple conglomerates and startups are exploring the space in their own ways, including AWS (with its Q assistant), Thoughtly, Observe AI and Sierra.

According to Gartner, by 2025, 80% of customer service and support teams will be applying generative AI in some form to improve agent productivity and customer experiences. 


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Data platform Airbyte can now create API connectors by reading the docs

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Data platform Airbyte can now create API connectors by reading the docs

If your startup is only remotely related to working with data pipelines, you’re probably trying to figure out how to capitalize on the current moment: Enterprises are trying to figure out how to best use data to power generative AI products, and to do that, they need robust data services. Airbyte, which launched in 2020, started with a focus on building a low-code/no-code open source data integration platform. Since then, Airbyte raised a total of $181.2 million, including a massive $150 million Series B round during the somewhat anomalous days of late 2021.

After four years, the company is now launching Airbyte 1.0 — and the focus, of course, is on AI, both as an addition to Airbyte’s own tools and to help its users build their own AI-based services.

Indeed, the company is now leveraging AI in a clever way to expand on its overall low-code/no-code philosophy: Its model will be able to look at the documentation for an API and automatically create a connector based on that. You simply point it at the documentation, and it’ll handle the rest (at least in theory; time will tell how well that works in practice, of course.)

As Airbyte co-founder and CEO Michel Tricot told me, he believes that one area where large language models are transforming how enterprise use their data is by making unstructured data far more useful — and usable.

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“Structured data is just the tip of the iceberg when it comes to leveraging data’s full potential,” he said. “With the rise of LLMs, we can now efficiently tap into previously untouched unstructured data. … We’ve seen massive demand for handling multi-modal data. Our latest developments have been geared toward supporting intelligent, context-aware pipelines, optimizing frameworks like RAG, and automating pipeline creation based on customer data workflows. These innovations are crucial to unlocking advanced use cases and enhancing LLM performance.”

Because Airbyte is now so much better at managing unstructured data, its users can now leverage their existing pipelines to do that, without having to rely on additional tools.

In non-AI news, Airbyte’s connector now also supports GraphQL, which should help users access many additional datasets without even having to build custom pipelines.

With this release, Airbyte is also making its self-managed enterprise service generally available. Like with so many open source companies, the enterprise version, which is available on the AWS and GCP marketplaces, will offer features like single sign-on (SSO) and role-based access control (RBAC), as well as Airbyte-specific features like sensitive data masking and advanced observability.

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Airbyte says it has 7,000 enterprise customers and has seen over 170,000 deployments by now. Its customers range from Calendly and Coupa to Perplexity AI and Siemens.

“Every company is a data company — to drive decision-making and as the foundation for AI initiatives,” Tricot said. “Only Airbyte, with our open source strategy enabling hundreds of connectors, can give enterprises the ability to leverage any data they choose. As AI continues to drive transformation, we’re delivering the technology and ecosystem required for organizations to build the data infrastructure needed for AI-driven innovation.”

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Types of Server Machines | Tower Servers | Rack Servers | Blade Servers

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Types of Server Machines | Tower Servers | Rack Servers | Blade Servers



What are the various types of server machines ? Which one is suitable for your business ?

tower server vs rack server vs blade server

सर्वर मशीन्स कितने प्रकार के होते हैं ? आपके बिज़नेस के लिए कौन सा सर्वर मशीन सबसे अच्छा रहेगा ?

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Ghost of Yotei is the next entry in Sucker Punch’s Ghosts series

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Ghost of Yotei is the next entry in Sucker Punch’s Ghosts series

To close out Sony’s State of Play presentation, Sucker Punch debuted a first look at the next game in its award-winning Ghosts series. Dubbed Ghost of Yotei, players will inhabit a new female protagonist named Atsu, who wields a shamisen in addition to a samurai’s traditional sword. According to the trailer description, Atsu will travel the wilds around Mount Yotei accompanied by a mysterious wolf companion.

Sucker Punch Studios, the developers behind the Sly Cooper and Infamous series, released Ghosts of Tsushima back in 2020. The game was praised for its quiet, contemplative moments as much as it’s Akira Kurosawa-style samurai action. Earlier this year, Sucker Punch released a PC port of Tsushima and confirmed that a movie based on the game is in the works, with John Wick director Chad Stahelski tapped to lead the project.

In the blog post announcing the game, Sony stated that Ghost of Yotei was Sucker Punch’s first game built specifically around the PS5. According to the developers, Ghost of Yotei will offer the same kind of beautiful observation moments as its predecessor while adding new features as well.

Ghost of Yotei
Image: Sony

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“We have massive sightlines that let you look far across the environment, whole new skies featuring twinkling stars and auroras, even more believable movement from wind on grass and vegetation,” said Andrew Goldfarb, communications manager at Sucker Punch. “Our new setting also gives us the opportunity to introduce new mechanics, gameplay improvements, and even new weapons.”

Sony didn’t share release date details, only pegging the game to a 2025 release window.

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Watch out Dyson: these 3 radically different hair dryers are making haircare exciting again

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Three hair dryers from IFA 2024 that impressed me; the Dreame Pocket (right) Laifen Mini (middle) and Shark FlexFusion (left)

There were plenty of devices at IFA 2024 that showed how technology in general is getting creative with form and function, but a lot of eyes were on the beauty space as it continues to radically reinvent what hair styling devices look and feel like. 

Gone are the days of conventional hair dryers being the market norm; the once iconic pistol-shaped handheld dryers are shifting into new form factors, making the best hair dryers interesting once again. 

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Dell Rack Servers | Price List | Refurbprice

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Dell Rack Servers | Price List | Refurbprice



#Dell #Rack #Servers | #PriceList | #Refurbprice

https://www.refurbprice.com/refurbished-dell-rack-servers-price-list

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Why Machines Learn: A clever primer makes sense of what makes AI possible

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Members of the medical staff at the Elithair clinic conduct an artificial Intelligence analysis of Felix Hofmann
Members of the medical staff at the Elithair clinic conduct an artificial Intelligence analysis of Felix Hofmann's scalp and his hair roots.

Machine learning is key to developments in medical diagnostics

Mario Heller/Panos Pictures

Why Machines Learn
Anil Ananthaswamy (Allen Lane (UK); Penguin Random House (US))

As someone who writes for a living, I routinely feel assaulted by the onslaught of generative artificial intelligence. How long before I become a mere massager of prompted paragraphs, the joy of creation abandoned in favour of more, faster, cheaper?

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Anil Ananthaswamy’s Why Machines Learn: The elegant maths behind modern AI won’t tell me or you about the future of AI in our society, nor what we should do about it. But whether you regard the algorithms used in facial recognition,…

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