Perceptyx Launches Perceptyx Anywhere to Help Organizations Build AI That Understands Their People

As large enterprises move from simply adopting AI tools to building and configuring their own AI assistants and systems, AI is increasingly being brought directly into workflows and organizational decisions. Simply connecting these systems to employee data and insights does not mean they can accurately interpret what that information means for a specific workforce. The harder challenge is developing AI that can understand employee voice and build intelligence specific to the workforce it serves.

Perceptyx Anywhere brings together three capabilities to address that challenge:

• Connect: Bring Perceptyx employee experience data, insights and action-planning capabilities into the AI systems organizations use and build through the Perceptyx MCP server and API layer.
• Evaluate: Use PYX Labs’ benchmarking, evaluation and post-training capabilities to measure and improve how accurately a company’s AI systems interpret employee feedback against expert I-O psychologist judgment.
• Predict: Develop workforce-specific intelligence using small language models (SLMs) trained on an individual organization’s employee listening data to identify patterns specific to that organization, including signals associated with regrettable attrition, productivity and disengagement.

“AI can retrieve employee data. That doesn’t mean it accurately understands employees,” said Ross Wainwright, CEO of Perceptyx. “As organizations become builders of their own AI agents and systems, they need more than access to another data source. They need confidence that AI can interpret employee experience accurately and develop intelligence specific to their workforce. Perceptyx Anywhere brings those capabilities together so organizations can move from access to understanding and, ultimately, workforce-specific intelligence.”

Connect employee intelligence to AI

Perceptyx Anywhere’s MCP server and APIs allow organizations to bring employee experience data and insights into the AI assistants, agents and applications they use or build.

This enables organizations to bring employee intelligence into existing AI workflows, so leaders can work with workforce insights where they already use AI rather than navigating to a separate EX application or dashboard for every interaction.

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Evaluate whether AI gets it right

Connecting employee intelligence to AI is only the first step. Organizations also need to know whether AI is interpreting that information accurately.

Employee feedback is inherently contextual and often subjective, making it particularly challenging for general-purpose AI models to interpret reliably. Yet, today, six in ten managers report already using AI to help make decisions about their direct reports, including promotions, raises, and terminations.

Perceptyx Anywhere brings this capability to organizations through PYX Labs, Perceptyx’s AI research lab. PYX Labs developed PYX-Voice, a benchmark designed to evaluate how well frontier AI models understand employee feedback. The benchmark has been used to test 20+ leading large language models across 84 employee listening tasks, showing that while models perform well on straightforward tasks, their performance can decline substantially when interpreting ambiguous and emotionally complex feedback.

That research gives Perceptyx the foundation to evaluate how AI interprets workforce intelligence, identify where it falls short, and improve that intelligence over time. Organizations can now apply this same approach to the AI experiences they build, using Perceptyx models, evaluation and employee experience expertise to improve how AI understands their workforce.

Predict what matters to your workforce

Perceptyx’s predictive SLMs take this approach a step further by making that intelligence specific to an individual organization. These models are trained on an individual company’s employee listening data and workforce outcomes, connecting signals across years of employee experience data, from onboarding and lifecycle feedback to pulse, census, and exit surveys, to identify patterns and make company-specific workforce predictions with greater precision.

By learning from the patterns specific to that workforce, these models can identify emerging signals associated with outcomes such as regrettable attrition, productivity and disengagement, and ultimately, make company-specific workforce predictions.

Each model is single-tenant and not combined with data from other customers.

Most EX platforms are focused on making employee data accessible to AI. Perceptyx is building toward AI that understands an individual workforce and can help leaders make faster and more informed decisions about what may be coming next.

“Employee sentiment and emotion are not typical data sets,” said Joseph Freed, Chief Product Officer at Perceptyx and Head of PYX Labs. “They are subjective, contextual and constantly changing. As AI takes on a greater role in understanding and making decisions about people, organizations need confidence that it is interpreting employee voice accurately. That requires more than access to the data. It requires the ability to evaluate how AI understands that data and improve it in the context of each workforce.”

Perceptyx Anywhere: AI that understands your workforce

Perceptyx Anywhere brings together the data, models, evaluation and employee experience expertise organizations need to build and use AI that understands their workforce.

Whether organizations are building their own AI experiences or adopting AI assistants and agents, Perceptyx Anywhere gives them a path from connecting AI to employee intelligence, to measuring and improving how it understands that intelligence, to increasingly tailoring it to the context and dynamics of their own workforce.

Perceptyx Anywhere makes that intelligence available wherever organizations use AI, while continuing to power the Perceptyx platform. Over time, organizations can move beyond simply giving AI access to employee data toward AI that can understand workforce context, identify meaningful patterns and help leaders see what may be coming next.