Verint’s recent Engage conference in Las Vegas marked its first since Thoma Bravo acquired Verint and merged it with Calabrio. The dominant message from the keynote stage was reassurance: no rip-and-replace, no forced migrations, and both WFM customer bases can remain in place. CEO David Rhodes leaned heavily into a “better together” narrative, citing a combined footprint of 40% WFM market share, 12,000 customers, 7 million agents, and 11 billion interactions. The messaging resonated with contact center leaders fatigued by agentic AI hype, reinforcing an outcome-driven strategy Verint has been steadily building, including embedded ROI calculators and a 90-day money-back guarantee.

Verint has been actively deploying a broad portfolio of purpose-built bots (more than 50) designed to execute specific tasks within customer care operations. But as enterprises scale bot usage, the challenge shifts to managing and orchestrating these agents through an underlying operational layer that can automate workflows within a configurable architecture accessible to CX business users.

Most CX vendors building on generative AI are grappling with the same issues: determining which models should power which use cases, ensuring resilience when model providers become unavailable, and avoiding the operational burden of constant prompt reengineering as models evolve. Verint’s approach is to abstract this complexity behind an AI-as-a-service layer that sits between its bot library and the underlying model ecosystem.

Agent Factory Signals the Shift from AI Features to Operational Control

At the event, Verint introduced Agent Factory, an orchestration environment for building, configuring, and managing a hybrid workforce of human and AI agents. It is structured around four core components:

• Prebuilt agents for common CX use cases, along with tools to create custom agents and route work to human agents when needed
• Centralized prompt management to support governance at scale
• Model flexibility, including bring-your-own-model support, to avoid dependency on a single LLM provider
• Data connectivity and governance embedded within the CX Automation Platform

Chief Product Officer Jaime Meritt framed this as a shift from “capabilities you can demo” to “outcomes you can measure.” In practice, Agent Factory serves as a control plane for Verint’s bot ecosystem, enabling enterprises to configure, govern, and orchestrate agentic workflows across both automated and human resources. This layer supports more adaptive CX processes, such as linking post-interaction summarization with automated follow-up actions triggered by real-time sentiment signals, effectively closing the loop between insight and execution.

Verint also introduced Desktop Intelligence, an AI-driven capability that analyzes screen-level activity to contextualize both conversational outcomes and the actions taken during each interaction. By correlating behavioral and conversational data, this approach extends the value of legacy interaction repositories and points toward operationalizing decades of previously underutilized enterprise data. It surfaces variations in how agents complete tasks, exposes shadow processes that never make it into formal training, and recommends more efficient workflows.

When combined with Workforce Intelligence (real-time intraday staffing adjustments aligned to business outcomes) and Quality Intelligence, the platform begins to connect agent actions directly to measurable impact. In one demonstration, the system identified and corrected a $500 refund mistakenly entered as $100 on the same day, before the customer noticed.

Validation: Customers Quantify the Shift to Outcome-Driven CX

Customer panels reinforced the outcome-oriented narrative with tangible results. BT’s Anthony Cass described a complex contact center environment spanning three brands, cross-skilled agents, and legacy systems. BT took a measured approach, starting with a 12-week coaching bot pilot and scaling in increments of 100 agents. By layering sentiment analysis and real-time coaching into a sales environment, BT achieved a $9 million uplift in cross-sell revenue and reduced time to competency for new hires by three weeks. Additional capabilities, including call summarization and a supervisor-to-agent simulation tool, are now in development.

Columbia Bank’s Laura Green outlined a different approach. Rather than a phased rollout, her team used AutoQM and Calabrio analytics to identify trending call drivers, implemented targeted changes, and reduced both call handling times and wait times. The next step is GenieBot, which will translate those insights into consistent, agent-level coaching.

Customer success with proven bots and outcome-driven messaging aligns well with a market increasingly skeptical of broad agentic AI claims. The more durable story, however, is architectural: Agent Factory introduces a governance and model-flexibility layer, while Desktop Intelligence demonstrates Verint’s ability to extract value from unstructured interaction data. Together, these elements, combined with an expansive automation portfolio and outcome-oriented go-to-market approach, position Verint as enterprises transition toward agentic AI as the foundation for next-generation CX orchestration.

Categories: Conversational Intelligence, Intelligent Assistants, Intelligent Authentication, Articles