May 26, 2026
Capacity Launches AI Analytics Assistant to Help CX Leaders Get Answers From Their Data Faster
AI-powered support automation platform Capacity has launched the AI Analytics Assistant, a new feature that lets customer experience, contact centre and operations leaders ask questions about their interaction data in plain English and get instant answers in the form of charts, reports and visual summaries.
CX Teams Are Struggling to Use Their Own Data
CX teams are drowning in data but still struggling to make sense of it. Across AI agents, human support conversations, ticket histories and backend workflows, interaction data accumulates rapidly, but it rarely ends up in a single, easy-to-use location.
Instead, it gets spread across disconnected dashboards, stored in formats that require technical expertise to interrogate, and processed through manual reporting workflows that eat up hours every week. The result is that leaders often lack the timely visibility they need to understand what is driving call volume spikes, which issues are pushing up escalation rates, or where automation is falling short.
Research from CCW’s State of Customer Management Report found that 48% of organisations report only occasional collaboration between their contact centres and other departments, while 34% admit that collaboration is minimal, which worsens the problem of scattered data and missed opportunities for improvement.
Real Answers, In Plain English
The AI Analytics Assistant sits on top of Capacity’s interaction data layer, drawing from transcripts, ticket metadata, workflow performance and bot usage data. Rather than navigating a series of pre-built dashboards, users can type a question such as “Why did call volume spike last Wednesday?” or “What issues are driving the most escalations?” and receive an immediate, visual answer. The underlying system does not require users to know where the relevant data lives or how to extract it; the assistant handles that automatically.
Several practical features accompany the core natural language capability. Users can pin key outputs to custom dashboards to track recurring questions and performance trends over time.
Dashboards can also be converted into shareable presentation views and exported as PDFs, making it easier to bring data into leadership updates, quarterly business reviews and executive briefings without rebuilding reports from scratch. Automated delivery is available too, allowing teams to schedule dashboards and reports to be sent to stakeholders on a weekly or monthly basis.
“Data Stuck in Dashboards Defeats the Purpose”
David Karandish, CEO and founder of Capacity, described the problem the feature aims to fix: “The purpose of having data across channels on every interaction is so leaders can make more informed decisions. But when that data is stuck in dashboards that are difficult to access or use, it defeats the purpose. Without fast, reliable access to the right insights, customers keep running into the same issues, and CX teams are left without a clear path to fix them.”
Capacity is rolling out the AI Analytics Assistant immediately to its existing customer base, which spans more than 20,000 businesses including DSW, Culligan, Choice Hotels and AAA. The company is betting on analytics visibility as a core part of what a CX automation platform should offer.
Where This Fits in the Wider CX Analytics Market
The launch adds to a growing list of AI-powered analytics tools entering the CX market, as vendors increasingly compete on their ability to turn raw interaction data into something actionable.
The smartest brands are already moving beyond retroactive measurement, using interaction data to spot patterns and solve problems before customers notice them, and tools like the AI Analytics Assistant make that kind of intelligence accessible without requiring a data science team behind it.
Whether natural language querying proves to be the answer many teams are looking for will depend on how well the assistant performs against the real-world complexity of large-scale contact centre data.
