The accelerating pace of digitalization has brought a stark reality into sharp focus: the immense cost of poor customer experience. A staggering $4.8 trillion annually — and growing — is siphoned from the global economy due to customer frustration. For the past decade, many enterprises have attempted to tackle this problem through Customer Data Platforms (CDPs) and enhanced customer service solutions. CDPs aim to unify customer identities and personalize communications, while modern contact centers provide agents with tools to better assist customers.

Yet, despite these significant investments, the pervasive frustration in the consumer industry remains at an all-time high. In travel and hospitality, a sector acutely impacted by customer sentiment, over half of travelers reported frustration with their experiences in 2023 — the highest across all consumer industries. This dissatisfaction translates into tangible losses: an estimated 64 million un-taken flights annually in the USA alone, costing the economy an estimated $71 billion.

Traditional solutions, likes CDPs, take months to implement, require multi-million dollar investments and often struggle with the dynamic, real-time demands of industries like travel. Contact center solutions remain prohibitively expensive.

However, the recent advent of generative AI offers a crucial reset button for the problem. At HyperTrail, we believe the critical metric to track isn’t the number of customer service calls a company can handle with AI, but the number of customer service calls that are never made because AI proactively anticipated and solved the problem. This brings us to the core of this discussion: Ambient Intelligence.

Earlier this year, a concept emerged from thoughtful discourse, notably articulated by Harrison Chase, LangChain’s CEO, describing “ambient agents.” These are AI agents that operate silently in the background, reacting to events within enterprise systems and taking proactive action to resolve anticipated problems. Unlike the more familiar conversational AI models like ChatGPT, ambient agents are an invisible intelligence, working behind the scenes to solve issues before the customer even realizes they exist.

For ambient agents to effectively act on behalf of an enterprise, they require real-time access to accurate, timely data. This is where we diverge from the traditional notion that a customer data platform or marketing solution alone can solve the entirety of the customer experience challenge. Our work with hundreds of companies within the experience economy has underscored a critical truth: truly end-to-end customer experience requires not only deep customer understanding in real-time, but also parallel, real-time insight into operational data.

Consider a passenger facing an airline delay. To genuinely help, the airline needs to understand the customer (are they traveling with children, for business, do they have flexibility?), but equally important, they need a real-time grasp of the operational state (probability of delay, airport congestion, staffing levels). Imagine an ambient agent proactively informing that traveler: “Based on current operations, including takeoff queue and staffing, we anticipate a three-hour delay. We recommend you get dinner now.” This level of proactive, context-aware service transforms a frustrating situation into a manageable one, a stark contrast to merely sending automated delay updates every 30 minutes.

To tackle the multi-trillion dollar problem of poor customer experience, enterprises need a data foundation that supports real-time access to all data — customer and operational. They need a digital twin of the entire enterprise that ambient agents can leverage to preemptively resolve issues before they escalate.

This is precisely what HyperTrail is. Our platform creates these real-time digital twins of entire operations and customer bases, allowing ambient agents to make informed decisions and act on behalf of the brand. To ensure trust and reliability, we’ve incorporated robust observability capabilities, enabling full traceability of events from source to agent action, with the ability to monitor effectiveness and even simulate agent behavior before deployment. This builds crucial confidence in the system’s ability to safely preempt and solve customer experience issues.

Furthermore, as the generative AI landscape rapidly evolves, we’ve designed HyperTrail to facilitate continuous optimization. Customers can create business-specific tests that evaluate ambient agents against new language models, allowing them to capitalize on performance or cost improvements without disrupting operations.

A significant pain point in past CX projects, especially CDP implementations, has been the laborious integration of dozens or even hundreds of disparate systems. At HyperTrail, we’ve adopted an AI-first approach with our proprietary generative connectors, which automatically generate and deploy integration code. This allows brands to integrate any source system into their digital twin platform in days, not months, empowering ambient agents with the real-time data they need.

Beyond this, HyperTrail offers capabilities to organize ambient intelligence use cases according to organizational design, ensuring accountability and clear ownership of these invisible problem-solving efforts. We are also developing intuitive querying capabilities to allow businesses to ask questions of their real-time data and assess the effectiveness of their ambient agents.

The $4.8 trillion cost of bad customer experience will not be solved by simply automating customer support. The true measure of success lies in the number of customer issues that never materialize because an ambient agent anticipated and resolved them proactively. Ambient intelligence empowers enterprises to adopt a proactive, rather than reactive, approach to customer experience. HyperTrail is building the first ambient intelligence platform for the experience economy, transforming frustration into foresight and driving unprecedented levels of customer satisfaction. Because the best customer service call, is the one that didn’t need to happen in the first place.