UKG unlocks real-time workforce intelligence at scale with the Agentic Data Cloud

Radhi Chagarlamudi
Group Vice President, Product Engineering, UKG
Heather White
Cloud Data Architect, Google Cloud
At UKG, we’ve spent years building and expanding our human capital management (HCM) and workforce management (WFM) solutions with new products, capabilities, and a series of acquisitions. Our cloud platform includes a suite of connected systems that support every corner of the employee experience, including scheduling and workforce operations, HR and payroll, and culture and engagement tools.
These connected tools offer customers incredible depth, but it also means our backend reflects years of evolution. We have 126 application teams, dozens of tech stacks, and more than 12,000 database instances inherited through acquisitions and product growth. And each product carries its own schema and operational footprint.
Previously, data moved through bespoke pipelines not built for real-time use. As AI advanced, expectations did too. Customers wanted instant insights across HR, time, pay, culture, and operations, and those insights increasingly needed to drive automated workflows and intelligent applications.
Internally, teams needed consistent, high-performance access to shared data to innovate faster and modernize our architecture. We needed a unified foundation for the next generation of intelligence across our suite. That’s why we built People Fabric, our new data and intelligence platform powered by AlloyDB for PostgreSQL and the just-announced Agentic Data Cloud.

Unifying the systems behind the suite
People Fabric started with a simple need: bring the full UKG suite onto one real-time foundation. Getting there started with defining a single canonical data model for the entire suite. This would serve as the shared language for people, work, pay, and culture data — consistent no matter where the information originated.
We needed an operational database that could ingest changes quickly and scale horizontally. That’s why we chose AlloyDB as the core of People Fabric. It gives us millisecond-level read-after-write behavior, high-throughput ingestion, scalable read pools, and native vector capabilities to support AI.
With the model defined and the operational store selected, the next step was building the pipeline that feeds the platform. We created a custom change data capture (CDC) framework to extract changes from our existing operational databases inherited over the years. Those changes flow through Dataflow, where they’re transformed into the canonical structure that AlloyDB for PostgreSQL expects.
Once in AlloyDB, that data becomes the real-time backbone of the platform. Applications use it for near-instant queries. AI agents rely on it for cross-domain decisions, and vector search engines use it to power natural-language and similarity-based experience layers.
For larger analytical workloads, the same data flows into BigQuery, which gives our teams and our customers the ability to perform organization-wide reporting and analysis without straining the system. Cloud SQL holds the metadata and tenancy context that govern who can see what and how different parts of the suite interact with People Fabric. From there, the system runs continuously. Data enters through streaming ingestion and gets modeled once in AlloyDB for PostgreSQL to make it available everywhere.
Bringing people intelligence to intelligent people
With the architecture in place, People Fabric gives us something we never had before: a complete and consistent view of people, work, pay, and culture data that’s updated continuously and ready for AI to use in real time.
That unified context is what powers our assistive experiences, including conversational reporting and natural-language interactions. Leaders can ask questions in plain English and get answers that reflect the full picture — not just a single system’s slice of it.
With the power of Google’s Agentic Data Cloud, our platform unifies analytical and transactional data to power real-time AI. This allows agents to reason over live workforce signals and trigger immediate actions. Because this data is governed and modeled from the start, our agents can reliably handle multi-step workflows across HR, payroll, and timekeeping.
Whether they're identifying pay discrepancies, adjusting schedules, or flagging compliance risks, they operate with the same shared semantics and security model that guides our applications. It’s the difference between AI that reacts and AI that can truly assist.
Driving impact across every layer
For engineering teams, People Fabric acts as a database-as-a-service that removes the need for each microservice to manage its own datastore or pipelines. This accelerates development and supports modernization without customer disruption.
AlloyDB for PostgreSQL delivers millisecond read-after-write behavior, zero replication lag, and near-real time ingestion latency, enabling real-time workloads with far less complexity. Migrating core person and employment data off our on-prem monolith has generated cost savings significant enough to fund half of People Fabric.
Real-time operational data now gives managers a live view of staffing, pay, and workforce activity. More than 1,000 organizations are already on the platform, with another 1,000 in progress.
As we continue expanding People Fabric, we’re laying the groundwork for deeper agentic automation, more responsive analytics, and a growing set of AI-driven capabilities — all on a trusted, scalable foundation built for what’s next.
Learn more
UKG’s success illustrates how leveraging AlloyDB for PostgreSQL and the Agentic Data Cloud allows organizations to unify operational and analytical data, creating the essential foundation for real-time, agentic AI.
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