As organizations evolve toward AI-first ways of working, People Functions face one of their biggest challenges: fragmented data and inconsistent definitions of key metrics.
“Every organization has a very unique definition to a particular metric, fragmented data systems and sources leading to inconsistent and slow decision making.”
– Ujjwal Sehgal, Global Head of People Analytics, Mars Inc.


As organizations evolve toward AI-first ways of working, People Functions face one of their biggest challenges: fragmented data and inconsistent definitions of key metrics.
“Every organization has a very unique definition to a particular metric, fragmented data systems and sources leading to inconsistent and slow decision making.”
– Ujjwal Sehgal, Global Head of People Analytics, Mars Inc.

To unlock trusted, contextual, and scalable decision-making with systemic AI, organizations must establish a semantic layer, a unified foundation that connects data, context, and intelligence.
“Unlike platforms or models you can borrow, the semantic layer reflects your organization’s unique intelligence — it’s the one thing that’s truly yours”
– Piyush Mundhra, Chief Customer Officer, MathCo

To unlock trusted, contextual, and scalable decision-making with systemic AI, organizations must establish a semantic layer, a unified foundation that connects data, context, and intelligence.
“Unlike platforms or models you can borrow, the semantic layer reflects your organization’s unique intelligence — it’s the one thing that’s truly yours”
– Piyush Mundhra, Chief Customer Officer, MathCo


What You'll Learn

Why Context Matters
and how it defines the success
of your AI initiatives
Architecture of
the Semantic Layer
in a People Function
How to Build It Right
aligning technical foundations
with adoption goals

Download the White Paper

