Conversational AI continues to see expanded adoption and innovation across industries. This past month we saw major players make big moves to advance and integrate conversational interfaces and assistants into their products and services.
As new developments demonstrate, conversational interfaces are becoming a central part of user experiences and business operations. We can expect to see rapid evolution in how AI assistants can provide more intuitive, contextual interactions. This newsletter will keep you up to date monthly on key trends, products, partnerships, and insights in this quickly growing field. Here are some of the top stories from August 2023:
Investment/Partnership Deals
Voiceflow, a startup enabling anyone to build conversational AI experiences, has raised $15 million in a funding round led by OpenView. This brings Voiceflow’s total funding to $35 million and values the company at $105 million post-money. The new capital will allow Voiceflow to expand its conversational AI platform. Most notably, Voiceflow plans to launch an AI builder powered by large language models like GPT-3. This will make it easier for companies to create chatbots and voice assistants leveraging the latest natural language processing technology. Voiceflow’s key advantage is flexibility — it allows customers to mix and match speech recognition models and AI frameworks. Companies aren’t locked into any single conversational AI vendor. The platform also features robust analytics and testing capabilities.
Hyundai Engineering Co., a leading engineering solutions company in South Korea, is partnering with Jenti AI, an AI research and development startup, to develop a conversational artificial intelligence (AI) program for the plant and construction sectors. Through this partnership, Hyundai Engineering plans to create a large language model that can understand complex questions and generate detailed, human-like responses about technical construction and engineering issues. The natural language processing would allow workers to get fast access to documents, data, and expertise by simply typing queries in plain language. The AI assistant is intended to enhance productivity, work quality, training, and risk management. By customizing conversational AI to its workflows, Hyundai Engineering hopes to spearhead the digital transformation of knowledge-intensive industries.
MSCI Partners with Google Cloud for Investment Conversational AI. MSCI, a major provider of investment decision tools, has expanded its partnership with Google Cloud to develop conversational AI and generative AI solutions for the finance industry. The collaboration will leverage Google’s Vertex AI platform and climate data technology to create tools that help investors better manage portfolio risks and opportunities. Key focus areas are conversational AI for natural language queries, generative AI for investment insights, and climate-related data analytics. By combining MSCI’s expertise in investment data and models with Google Cloud’s capabilities in AI and cloud computing, the partners aim to provide investors with enhanced data-driven decision making through intuitive conversational interfaces. This partnership exemplifies the growing role of AI, particularly natural language processing, in transforming the investment sector by making complex data more accessible.
SoundHound Powers Voice Assistant in New Togg Smart Vehicles. SoundHound AI has partnered with Turkish automotive company Togg to deliver an AI-powered voice experience for their new line of smart vehicles. SoundHound’s technology, including Edge+Cloud connectivity and multi-language capabilities, enables Togg’s custom-branded assistant to understand natural speech commands for music, climate, navigation, and more. The intelligent assistant leverages SoundHound’s proprietary Speech-to-Meaning and Deep Meaning Understanding engines to provide contextual responses to complex queries before users finish speaking. With support for 25 languages, the collaboration offers Togg drivers and passengers an effortless way to control in-car features conversationally. As vehicles get smarter, voice AI delivers more intuitive, human-like interactions. SoundHound’s platform integrates with next-gen components to optimize the mobility experience. Expect more automakers to follow Togg’s lead in providing branded voice assistants that make driving safer and more enjoyable.
Apple is making major investments in advancing conversational artificial intelligence. The tech giant is spending millions of dollars per day training sophisticated natural language models that could power more capable voice assistants like Siri. While Apple’s Foundational Models team working on conversational AI only has 16 people, the monetary investment is massive. Apple is leveraging large amounts of computational power and data to train advanced AI systems. The goal is to eventually enable Siri to understand multi-step requests and automate complex tasks through voice commands alone. Apple’s internal Ajax chatbot has been trained on a dataset of 200 billion parameters. As Apple continues to pour resources into conversational AI, we can expect more human-like interactions with Siri and potentially new creative media applications. The competition to develop the most capable AI assistant is continuing to heat up.
New product features, highlights & use cases
India is set to introduce conversational AI payments to its popular Unified Payments Interface (UPI) system. The Reserve Bank of India aims to add conversational capabilities to the 300 million active UPI accounts, which currently power instant digital transactions between consumers and businesses. Able to facilitate both C2C and C2B transactions, the addition of conversational payments to the system is anticipated to further the penetration of financial services in India. Conversational payments can enhance UPI’s ease of use and expand its reach. For a country still building out access to digital finance, voice-enabled transactions could prove crucial. India is now on the cutting edge of leveraging AI to boost financial inclusion. As other developing economies look to expand digital payments, India’s upcoming conversational UPI could serve as a model for meeting users’ needs with intelligent, conversational interfaces.
Enterprise automation provider EvoluteIQ has unveiled new conversational AI capabilities in its latest platform release. The EIQ 6.0 update includes GIQ Copilot, a new module enabling conversational interactions to build workflows, forms, rules, and applications using natural language commands. This launch aims to advance EvoluteIQ’s vision for end-to-end intelligent automation by integrating generative AI. Users can leverage models like GPT-3 to generate content and accelerate development. EvoluteIQ is focused on democratizing access to AI so any employee can drive digital transformation. With its low-code/no-code platform and emphasis on usability, EvoluteIQ wants to make AI-powered automation more approachable. Its latest release suggests conversational interfaces will become integral for enterprise automation. Enabling employees to collaborate with AI systems conversationally could significantly enhance productivity.
Timpi, a first of its kind decentralized online search engine has announced Wilson, a new conversational AI tool prioritizing user privacy, diversity, and real-time insights. Wilson taps into Timpi’s decentralized web-scale data index to enable informed, dynamic conversations on current events and trends. It also analyzes businesses’ online presence to engage in precise customer support dialogues. Timpi is incorporating Wilson directly into its search engine for seamless conversational experiences. A key differentiator is Wilson’s customizable responses, allowing users to adjust tone and relevance to their needs. Timpi envisions Wilson accommodating diverse communication styles in the future. The launch represents a major step toward decentralized, democratized conversational AI that emphasizes user control.
Product analytics startup Sprig has unveiled a new capability called AI Analysis for Surveys, which applies conversational AI to survey results. The feature allows companies to ask questions about their survey data and receive automated insights from Sprig’s natural language model. Sprig’s generative AI can analyze both quantitative and qualitative survey responses to uncover patterns, themes, and recommendations. This essentially transforms static survey data into an interactive, conversational interface. With major new customers like PayPal, Peloton, and Figma on board, Sprig is gaining traction in using AI to extract more value from user research. Its conversational approach to survey analysis provides on-demand access to insights that drive product strategy. Sprig’s latest innovation highlights the potential of generative AI to make market research more intuitive and actionable.
Skillsoft Launches CAISY to Hone Business Conversation Skills. Corporate training provider Skillsoft has introduced a new AI-powered conversation simulator, CAISY. The interactive tool helps professionals practice and improve business discussion abilities through personalized feedback. Users select conversation scenarios like coaching, change management, and product launches. CAISY then rates performance and provides tailored tips to optimize future interactions. The simulator features practice and role model modes, plus “behavior profiles” that mimic responses like defensive or dismissive. As communication remains vital for career and organizational success, CAISY offers a safe space for employees to develop this timeless skill. By rehearsing tough talks with AI, professionals across roles can hone conversational skills critical for leadership. As natural language AI advances, expect more immersive, conversational training applications like CAISY. Skillsoft is leveraging AI’s potential to make soft skills building more engaging and effective.
Conversational AI provider Gupshup unveiled new large language models tailored for specific business functions and verticals such as marketing, commerce, support, HR & IT, and industries like banking, retail, utilities and more. Dubbed ACE LLM, these natural language models aim to enable more natural, precise conversations across the customer journey. Available in 7 to 70 billion parameters, ACE LLM supports over 100 languages while built-in safeguards eliminate irrelevant responses. Enterprises can combine the models with internal knowledge bases for highly accurate, conversational interactions with context. ACE LLM also enables controls around tone, accuracy, data boundaries, and analytics. Gupshup offers flexible deployment options including public cloud and private cloud. With industry-specific LLMs, companies can now customize conversational AI to their unique needs and data. Tailored language models promise more coherent bot interactions across sales, marketing, support and other key workflows.
Talent assessment platform Harver has unveiled Harver CHATTM, a conversational AI tool aimed at optimizing candidate engagement during hiring. The chatbot automates screening with natural language conversations, dynamically collecting required details and answering live candidate questions. Harver CHATTM provides a smoother, more satisfying application experience that matches company branding. It can be embedded in existing flows or act as a standalone widget. The AI is configurable so employers can customize topics and train responses. Early users have seen dramatic reductions in time-to-hire and over 60 hours of saved recruiting time per role. Harver CHATTM also earned a high 4.7 candidate satisfaction score. By automating screening, the chatbot enables recruiters to focus on high-value activities. As competition for talent grows, conversational interfaces like Harver CHATTM will become key differentiators in hiring. AI-powered experiences boost efficiency while reflecting brand values.
SoundHound Launches Fully Automated Customer Service Voice AI. Voice AI leader SoundHound has unveiled Smart Answering, enabling businesses to instantly set up AI-powered call answering. Leveraging natural language processing and SoundHound’s conversational AI, Smart Answering provides customized, automated responses to customer inquiries with the same or better quality as human agents. The subscription service pulls relevant information from company websites to update its knowledge base. It can handle multiple simultaneous calls and SMS-based interactions. Smart Answering aims to optimize human labor by managing routine calls so staff can focus on higher-value work. As consumers increasingly prefer automated customer service, SoundHound’s conversational AI delivers. With quick onboarding and over 500 calls managed per customer monthly, Smart Answering makes sophisticated voice AI accessible for organizations across sectors. The launch represents a major step toward customizable, instantly deployable automated call centers.
Skit.ai Partnership Showcases Voice AI Impact in Collections. Conversational AI provider Skit.ai has teamed up with revenue recovery services provider for healthcare, government & financial companies, LJ Ross Associates to deploy its voice AI solution. By leveraging Skit.ai’s natural language platform, LJ Ross aims to boost scalability and efficiency amid industry talent shortages. Since implementation, LJ Ross has seen a 92% increase in connectivity and 18% rise in right party contacts. The 24/7 automated call answering improves availability while optimizing human agent time. This collaboration demonstrates voice AI’s potential in accounts receivable management. By resolving staffing and cost challenges, Skit.ai’s augmented voice intelligence enables LJ Ross to gain a competitive edge despite market consolidation. As consumers increasingly prefer conversational interfaces, voice AI delivers more positive collection experiences. LJ Ross’s success illustrates how AI partnerships can drive innovation and performance, even against larger competitors. Adoption of platforms like Skit.ai’s will be key for collections leaders seeking to leverage technology for sustainable advantage.
Let’s decode conversational AI!
In our modern, fast-paced world, having a quick and efficient way to communicate with technology can make all the difference. This is where conversational AI comes into play, serving as your digital assistant, customer service agent, and even as a chat companion.
But what makes conversational AI tick? What’s happening behind the scenes when you ask Siri about the weather or when a chatbot helps you book a hotel room?
The ABCs: NLP, NLU, and NLG
Natural Language Processing (NLP): It is a field at the intersection of computer science, artificial intelligence, and linguistics. Its ultimate objective is to enable computers to understand, interpret, and produce human languages in a way that is both meaningful and useful. Example: When you use a search engine, NLP algorithms work behind the scenes to understand your query and to rank the search results.
Natural Language Understanding (NLU): NLU is a subset of NLP and focuses on the machine’s ability to understand and comprehend human language. It is concerned with the ‘input’ side of the conversation. Example: When you ask a voice assistant like Siri or Alexa to “set an alarm for 7 AM,” NLU algorithms work to understand that the “intent” is to set an alarm, and the “entity” (i.e., the specific detail) is 7 AM.
Natural Language Generation (NLG): NLG is another subset of NLP but focuses on the ‘output’ side of the conversation. It is the aspect that allows the machine to generate a human-like response based on the understanding gained through NLU. After a voice assistant understands your command to “set an alarm for 7 AM,” the NLG part would be responsible for generating the response, such as “Okay, your alarm is set for 7 AM.”
Conversational AI systems rely on a combination of natural language processing (NLP) techniques to enable human-like interactions. Specifically, natural language understanding (NLU) and natural language generation (NLG) are key to providing both comprehension of user input and formulation of relevant responses. Each plays a crucial role in the development and effectiveness of conversational AI systems.