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No Jitter Roll: Salesforce Rolls AI into Sales Cloud and Service Cloud, Vonage Adds Omnichannel CX to its Portfolio, NEC Makes Its Own LLM Available
Welcome to this week's No Jitter Roll, our regular roundup of product news in the communication and collaboration spaces.
This week, NJR highlights Salesforce's integration of Einstein GPT into its Sales Cloud and Service Cloud products, while Vonage adds omnichannel CX capabilities to its Conversational Commerce solution, and NEC makes its proprietary LLM available as a service via Microsoft Azure OpenAI. Finally, Colt bucks this week’s trend of AI news by connecting its network to platforms from companies such as Genesys, Twilio and Zoom.
Salesforce Features Generative AI in Sales GPT and Service GPT
The CRM provider announced the integration of its Einstein GPT generative AI solution with Salesforce’s Sales Cloud and Service Cloud offerings. Sales GPT will use generative AI to auto-generate customer emails, create call transcriptions and summaries, summarize account-related research and history and draft contract clauses. Service GPT will auto-generate service replies, generate summaries of service cases and customer interactions, automatically construct knowledge articles based on customer interactions, and generate “briefings” for field service teams that summarize the work to be done at a customer site.
- In June 2023, Salesforce launched AI Cloud which incorporates gen AI across its portfolio, as shown above.
Want to Know More?
Check out these articles about generative AI:
- How Salesforce's Einstein GPT Works: There are some key, customer-friendly differences between the Salesforce implementation of generative AI and the more broadly available ChatGPT
- Generative AI and Data: Critical Elements for Future CX: Generative AI is only as good as the data it draws on. How can we optimize to integrate and maintain quality data?
- The Good, the Bad and What We Can Do with Generative AI: Generative AI-based chatbots cannot think, reason, or show emotion. Be careful with all the latest technology and stay in control of its answers.
Vonage Adds Omnichannel CX to its Conversational Commerce Solution
Via its Jumper.ai technology, the cloud communications provider has added new features to its Conversational Commerce solution that enable it to span multiple CX channels. For example, the Vonage Conversational Commerce (VCC) mobile app for iOS and Android allow agents to offer customer support with the same access to functionality, resources, CRM and customer information available on the Jumper.ai unified dashboard.
The new VCC Attentive Widget enables businesses to embed instant messaging widgets (powered by AI-driven bots) on their websites. VCC also now supports SMS and Google Business Messenger. VCC also now offers three modular packages that enable full broadcast and live chat capabilities. These include Notify, for notifications, Engage, which allows the creation of bots to power FAQs and customer support, and Convert, which includes commerce and payment capabilities.
- No Jitter contributor Dave Michels provides commentary on “conversational commerce” in his article about Vonage’s acquisition of Jumper.ai in 2021 as well as Ericsson’s acquisition of Vonage in late 2021. This trifecta of Vonage coverage by Michels concluded in July 2022 with his discussion of Ericsson completing its Vonage purchase.
NEC Develops and Provides Generative AI for Business Use
NEC Corporation (NEC) announced its new "NEC Generative AI Service" which will begin providing licenses for proprietary large language models (LLM), dedicated hardware, software, consulting services. The service will first become available in Japan and then expand to new markets after FY2024. This service leverages Microsoft Azure OpenAI Service and NEC's LLM.
NEC also established its “NEC Generative AI Hub” which consists of researchers, prompt engineers, consultants, digital trust specialists and other professionals, who will lead workshops to develop LLM use cases and strategies for customer, demonstrate how NEC’s LLM can be used and tuned/adapted to customer needs, and provide training sessions.
In its press release, NEC said it began deploying generative AI for internal business use in May 2023. The service was linked to internal systems such as internal chat and web conferencing tools, and is being used by about 20,000 users, or about 10,000 times a day. NEC stated said the following results have been noted so far:
- 80% reduction in man-hours required to create source code for internal system development.
- 50% reduction in the time required to create documents.
- A reduction in the time required to take detailed meeting notes from an average of 30 minutes to approximately 5 minutes.
Want to Know More?
- Five Ways Generative AI Will Change Collaboration: Generative AI offers incredible potential to improve productivity, operations, and security.
- Amazon Web Services Flexes Its Generative AI Muscles: Amazon Web Services (AWS) launched several new products designed to make generative AI more accessible and affordable.
Colt Expands Cloud Voice Services to Genesys, Twilio and Zoom
The UK-based digital infrastructure company announced Colt Cloud SIP, a new service that connects the Colt IQ network to platforms from companies such as Genesys, Twilio and Zoom. Colt also extended its Teams voice activation, through Direct Routing and Operator Connect to three new countries: Slovakia, Luxembourg, and Norway.
This Week on No Jitter
In case you missed them, here are some of our top stories for the week:
- Managing AI Tools Requires More Data Transparency: When deploying products and services with AI embedded into them, organizations must be sure that they can avoid unintended consequences from biased algorithms, faulty training, or incomplete parameters.
- The Self-Service Revolution for the Modern, Digital Contact Center: Companies can leverage self-service to provide seamless customer service to some people, while still providing agents for complex cases.
- Getting Beyond AI Hype: What to Consider in Training and Knowledge Bases: The training models in generative AI are only going to be as good as the quality of the complex training models upon which they are instructed. In other words – garbage in, garbage out.