Valérie Bécaert contains multitudes. By day, she’s vice president of ServiceNow AI Research, hunting for breakthroughs before anyone else sees them coming. By night, she paints, acts in plays, and performs with her band, Deep Yearning.
To Valérie, these pursuits aren’t as different as they might seem. "My love for the arts and for AI research actually enhance one another," she says. "Both are about finding patterns others miss: a gesture on stage, a brushstroke on canvas, a signal buried in data." That instinct to uncover hidden meaning, she explains, is what drives her work.
It's also what led her to build AgentPoirot, a pathbreaking AI agent designed to help organizations make sense of their data.
Most of today’s organizations are data rich and insight poor. They collect enormous volumes of information across HR, IT, finance, and operations. Nearly two-thirds of organizations manage at least one petabyte of data, according to data management and data governance company AvePoint. Turning it into something meaningful takes time, expertise, and resources most teams don't have.
"Our customers sit on a gold mine of data, but they don't have time to dig in and find meaning," Valérie says. Any potential insights are buried under layers of noise.
Consider what that looks like in practice. A spike in employee attrition shows up on an HR dashboard. A cluster of IT tickets starts accumulating. Customer satisfaction scores begin drifting downward.
Each data point, in isolation, looks like noise. But underneath the surface, patterns are forming. Together, they’re early warning signs of problems that will snowball into something much more dramatic if they’re left unaddressed.
For years, that work fell to data scientists: specialists who could sift through complex datasets, build models, and surface patterns invisible to the naked eye. But as the volume of data has increased, this work has multiplied far beyond what humans are capable of performing. The result is a widening gap between the data that organizations have and the decisions they’re able to make.
Valérie and her team built an AI agent to close that gap, and they named it after the most famous detective in fiction: Hercule Poirot, immortalized in classic novels by Agatha Christie, including Murder on the Orient Express and Death on the Nile.
The reference is apt—and not just because Valérie, in addition to her other pursuits, enjoys a good detective story. Like its namesake, AgentPoirot excels at sniffing out clues, following leads, and investigating issues at hand.
Using the data that businesses produce every day, the agent is designed to quickly surface trends and predict what might happen next. AgentPoirot can explore questions that would otherwise require significant analytical horsepower, such as:
- Is low PTO usage linked to elevated burnout in engineering teams?
- Are certain patterns in IT ticket volume predictive of downstream outages?
- Are there correlations between onboarding experience and first-year retention?
AgentPoirot digs in automatically, extracts meaningful patterns, and delivers answers that anyone can act on. The operator—the person who asks the AI agent a question—doesn’t need to know how to write a single line of code or to configure a data model.
The goal, Valérie says, is to make deep insights accessible to everyone, not just people with a data science background. That democratization matters. When the ability to ask and answer complex questions is limited to a handful of specialists, entire organizations lose out. AgentPoirot puts that capability in the hands of the people closest to the problems, at the speed those problems actually move.
For Valérie, AgentPoirot provides an exciting glimpse into where AI is headed.
As organizations continue deploying autonomous agents across the enterprise, the most powerful ones will move beyond execution and into reasoning, investigation, and illumination. They’ll do the detective work that turns raw data into decisions, and decisions into action.
There’s something fitting about the fact that this vision came from someone with a deep appreciation for the unexpected rhythms that make art in all its forms come alive. It’s no wonder Valérie’s AI agent applies the same philosophy to data as she does in her painting, acting, and music. "It's all about finding the patterns others overlook," she says.
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