Rippling's go-to-market organization depends on timely, trusted data to personalize outreach, prioritize accounts and move quickly as new opportunities emerge. As the company scaled, traditional reporting workflows could no longer support the real-time analytics required by 2,800 operators across growth AI and analytics teams and a growing set of AI agents. By building a unified GTM AI platform on Databricks and integrating Genie Agents into GrowthOS, Rippling created a governed conversational interface that delivers trusted business insights in seconds.
Building a real-time intelligence layer for GTM
Rippling’s mission is to free smart people to work on hard problems. The Growth Engineering team wanted to bring that same philosophy to its go-to-market organization by reducing the manual work required to collect data, write SQL and assemble context before teams could take action.
Sales, marketing and operations teams needed immediate answers to questions that shaped GTM execution, including:
Which accounts were showing buying signals
How campaigns were influencing the downstream revenue
What messaging resonated most with prospects
Which accounts and contacts represented the best next action
What context should drive personalized outreach with a compelling reason to help people adopt Rippling
Rippling also needed AI agents to operate on the same trusted data foundation, enabling them to automate analysis and surface insights in real time.
The challenge was that the existing data architecture was built for traditional analytics rather than real-time AI workflows. Data moved through multiple ingestion tools, transformation layers and scheduled pipelines before reaching downstream reporting systems. That introduced latency, fragmented business logic across tools and made it harder to serve governed insights consistently across both employees and AI agents.
As Rippling pushed further into AI-enabled GTM, the gap between reporting and action became harder to ignore. The organization needed a unified foundation where data could be trusted, queried instantly and used consistently by both people and agents.
“We didn’t just want faster dashboards,” said John Kutay, Head of Growth Engineering at Rippling. “We wanted a real-time intelligence layer where both GTM teams and AI agents could operate on the same governed source of truth the moment signals appear in the data.”
Genie brings governed conversational analytics to GrowthOS
Rippling rebuilt its GTM data platform on Databricks using a medallion architecture, Lakeflow Spark Declarative Pipelines, Delta Lake and machine learning pipelines that continuously process first-party and third-party data.
At the center of the experience is GrowthOS, Rippling’s internal AI application that gives more than 2,800 GTM employees a single place to interact with trusted business data. Rather than navigating dashboards or writing SQL, employees can ask questions in natural language while AI agents access the same governed data through the Genie API.
Creating a trusted foundation for people and AI agents
Before those insights reach users, Rippling applies machine learning-based entity resolution to reconcile customer and prospect records across hundreds of millions of records from internal systems and third-party data providers. By resolving duplicate identities into a single trusted record with confidence scoring, the company gives both employees and AI agents a consistent foundation for analytics and automation.
“Genie became the conversational layer for our GTM AI platform, giving teams and AI agents access to trusted data through a single, governed interface,” said John.
Genie Agents now power natural-language analytics across a wide range of use cases within GrowthOS. Employees can use plain language to:
Analyze campaign performance
Understand customer sentiment
Investigate sales objections
Retrieve account intelligence
AI agents use the same governed interface to support automated workflows across the customer lifecycle.
Because Genie sits directly on top of governed data, Rippling can continuously improve prompts, semantic definitions and business logic through Genie while maintaining centralized governance across the organization.
To support those experiences, Rippling also built semantic search using Databricks AI Search. Rather than recomputing embeddings every time someone asks a question, the team created an AI-ready retrieval layer that enriches conversations during ingestion and serves grounded results through hybrid search. Their internal principle became DRY(E): Don’t Repeat Your Embeddings.
The result is faster retrieval, lower inference costs and more consistent answers for both employees and AI agents.
A foundation for agentic GTM
Today, more than 2,800 employees use GrowthOS to access governed business intelligence powered by Genie.
The platform has become the foundation for multiple AI experiences across Rippling’s go-to-market organization, from conversational analytics to audience creation, account planning and campaign analysis. Sales and marketing teams spend less time collecting information and more time acting on it because they can retrieve trusted insights through a single conversational interface rather than stitching together data from multiple systems.
During staged A/B testing, Rippling measured gains from AI-driven personalization built on its unified GTM platform, including:
33% increase in demos booked
20% increase in new opportunities
The company also reduced reliance on manual GTM workflows.
The platform also went from essentially zero to a core piece of production infrastructure used across operations, data science, growth marketing and growth engineering in less than three months. Personalized, research-backed sales plays became cheaper and dramatically faster to generate.
“The real advantage is that we can reuse the same foundation across very different GTM problems,” said John. “Once the data is resolved, enriched and available to agents, we can focus much more of our energy on the experience we want to build.” For Rippling, the goal is to make governed data, machine learning, semantic retrieval and conversational analytics available as reusable building blocks so teams can quickly build new agentic GTM experiences.
FAQ: Rippling and Genie on Databricks
Genie is a conversational analytics capability built into the Databricks Data + AI Platform. It allows business users and applications to query governed data using natural language while maintaining centralized governance and security.