What happens when the “Platform of Platforms” goes deep into conversations between agents and customers or employees? For ServiceNow the hope is to radically accelerate AI agents’ capacity to comprehend in meaningful ways and perhaps, find new ways to initiate, optimize and even correct workflows that happen as a result to knowing just a little bit more than the other guys. To read the press release and Insights coverage.
What we know about the deal: ServiceNow has signed an agreement to acquire Belmont, CA based conversational intelligence firm, Cuein AI. Freshly dubbed a “conversation data and analysis platform” those of us in the service space will recognize the solution's capacity to ingest, analyze and action on customer conversations across a broad range of platforms, including interactions with chatbots and Interactive Virtual Assistants (IVA). While no financial terms were disclosed in the announcement, we do know that the company’s primary investors were Lightspeed Venture Partners, Khosla Ventures and Webb Investment Network…with additional investment by ServiceNow and Salesforce...so it shouldn't go unnoticed that ServiceNow may have beaten Salesforce to this punch.
What makes Cuein AI so interesting: What started as an AI tool to unlock the sentiment, intelligence and actionable real-time moves organizations could be making thanks to chat transcripts and data has turned into a more comprehensive conversation analysis solution. While Cuein absolutely mines chatbot engagements for actionable cues and signals from customer interactions with agents, it has taken analytics farther by looking beyond the lagging indicators of experience like the post engagement survey and set AI to work to infer customer satisfaction measures and foster action and change. For contact center customers, Cuein holds the promise that customer conversations in any channel, including voice, can be more than just ingested and analyzed for post-mortem understanding. Their voice analytics visualizes the flow of conversation and identifies real time trends, patterns and proactively alerts when those patterns are actually problems. But beyond the contact center or service environment, Cuein could be a very interesting optimization superpower for ServiceNow and their AI agents.
For Service and Experience Leaders: While Cuein has been on the radar—not to ruin the surprise, but they were included in the consideration group of 20+ stand alone offerings for an upcoming new shortlist focused on Conversational Intelligence in Customer Service—with integrations with CCaaS and CRM solutions like 8x8, Genesys, Microsoft, NICE, Salesforce and Zendesk along with LLM and model companies like OpenAI, Cognigy and Amelia, they were an emerging conversation and not quite yet a household name. ServiceNow did not include any statement of intention for what will happen to Cuein and if existing customers like Anthropologie, Crocs or Voya Financial would continue leveraging the solution outside of a ServiceNow environment. So…for existing customers...stay tuned is the message here. However, if you are a ServiceNow customer, now is the time to start thinking about which part of your workflows, your applications and your AI-powered bots could benefit from some self-awareness and self-healing. Where Cuein shines is in the ability to identify breakdowns and bottlenecks in conversations, providing much needed understanding into everything from how a bot is addressing customer needs to how product could be improved. Appropriately applied, Cuein should be using conversation for intelligence as opposed to a solution that is really narrowly focused on intelligence from conversations. And yes, it’s a nuance, but it is an important mindset shift. Intelligence from conversations only improves future performance of a bot or an agent. Conversations for intelligence turns conversations between any two points including between customers and bots, customers and agents, or agents and bots and turns it into a treasure trove of data which not only turns into enterprise-wide intelligence but also becomes a closed loop of knowledge to optimize conversations in-flight.
For AI, IT, Digital and Transformation Leaders: Cuein is about more about continuous improvement than it is about a tool for a specific function. In an age when agentic AI is being infused in almost every process and every interface in the enterprise, mining for patterns, flows, breaks and failures should be one of those ambient processes focused on improvement and optimization rather than reporting and post mortems. When a bot is delivering less than optimal results. In study after study, customers are admitting that there is far less leeway for agentic or bot-based failed experiences. After a bot fails to resolve and issue or provide contextually accurate and valued outcomes, a customer will not use that technology again and will double-down on the demand for a live-agent experience. Bottom line: bots have one shot where humans would typically get another chance. This is where AI intelligence data comes into play to diagnose, alert, prompt or even provide recommended fixes to ensure that design and optimization is fluid and continuous.
Parting Thoughts: ServiceNow has always taken its vision of being the central hub for work and workflows seriously. It shouldn’t be a shock that accelerating their Agentic AI roadmap is their starting point for 2025. While the lowest hanging fruit will be those customers looking to create feedback, intelligence and optimization loops for Agents, the fast opportunity for ServiceNow could actually be back at their roots of service. For far too long we have taken a test-deploy-review-reset approach to bot deployment and optimization. But agentic AI and this age of generative AI as a foundation for multi-modal multi-channel engagements with customers, waiting for a report is already too late to resolve negative outcomes caused by hallucination or broken process. In flight optimization and the replication of a live-agent’s capacity to problem solve in the moment is the new tech requirement. And in the end, it is yet another way AI organizations can reveal and integrate another critical data source by turning chatter into data.
