Level AI Launches AI Workers for Customer-Centric Teams
Level AI, the customer intelligence platform for enterprise contact centers, today announced AI Workers, a suite of specialized AI agents each scoped to a specific customer-centric role, automating the research, analysis, and planning workflows that consume the majority of time for coaches, analysts, QA leads, and CX executives.
Nearly 100 enterprise contact centers are already running AI Workers, with more than 25,000 Worker runs executed and overwhelmingly positive user feedback. Teams at Smartsheet, VistaPrint, and Ollie Pets use them in daily operations.
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AI agents are rewriting how enterprises operate, from coding agents producing over 80% of code to legal agents handling deep research and review. In customer experience, that investment has gone almost entirely to the front office. Over the past decade, enterprise CX has invested billions in voice bots, chat deflection, self-service portals, and IVR routing. But the people running operations behind those interactions received none of it.
General-purpose AI tools haven’t met this need. They solve for shallow extraction: summarize a call, tag a sentiment, but don’t account for scoring rubrics or the workflows that connect an insight to a coaching plan, a quality trend, or a product fix. In fact, 56% of CEOs report no measurable return from AI investments (PwC Global CEO Survey, 2026).
“Every AI tool CX operations has been given stops at summarization,” said Ashish Nagar, CEO and co-founder of Level AI. “The actual workflow, from insight to coaching plan to quality improvement, still runs on manual effort.”
Each AI Worker owns a defined job, produces a specific deliverable, and runs on the same customer intelligence data that an organization’s QA and analytics teams already use. The launch includes:
- Coaching Plan Worker which reads every interaction for an agent and produces a structured coaching brief with specific calls, moments, and talking points
- Conversation Research Worker which searches transcripts semantically and produces thematic research reports with direct customer language
- Executive Research Worker which runs multi-step investigations across data domains and synthesizes cited long-form reports
Additional workers at launch include the Conversation Analytics, Team Performance, Product Feedback, Resolution Insights, Sentiment Insights, iCSAT Insights, and VoC.
AI Workers run on a shared intelligence layer that links conversations and transcripts, QA frameworks, CRM records, team hierarchy, and AI-enriched signals such as sentiment, effort, resolution outcomes, and VoC themes. Every worker draws from the same scored and structured data that existing QA and analytics programs rely on, with no parallel data pipeline or reconciliation step.
A dual retrieval system searches transcripts and queries structured data in the same request, while a multi-agent orchestration layer breaks complex queries into parallel sub-tasks. Every output traces back to the source data it came from.
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An enterprise benefits administration company that deployed AI Workers during beta reported that surfacing performance data and coaching opportunities through a single prompt fundamentally changed how their team prepares for client conversations.
Their VP of Member Experience notes, “Having that level of information at our fingertips allows us to bring data and trends to our clients or use it internally for coaching on individual strengths, weaknesses, or opportunities within the tool. It has been really cool to work through.”
“Contact centers ran out of headcount strategies years ago,” said Nagar, “Enterprise software is shifting from a system of record to a system of action. A copilot doubles a person’s throughput at best. A worker creates a new line on the org chart. That is the operating model CX leaders need, and what this category is for.”
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