Evercore: ServiceNow's Data Business Is on Track for $1B+ ARR, and the Moat Is Bigger Than Investors Realize
Evercore Global TMT Conference, June 3, 2026 — ServiceNow EVP Gaurav Rewari outlines why the company's data and analytics platform is becoming a distinct revenue engine, not just an AI enabler
A New Business Already Approaching $1 Billion
The headline number from the Evercore Global TMT Conference is simple and significant. Gaurav Rewari, ServiceNow's EVP and General Manager of Data and Analytics, told Evercore analyst Kirk Materne that the company's data and analytics business is "on track to break $1 billion-plus in ARR in just a few quarters." For a business that Rewari describes as "relatively new" and previously "fairly scattered," that trajectory demands attention from investors who may still think of ServiceNow primarily as an IT service management platform.
Rewari was recruited directly by CEO Bill McDermott and President Amit Zaveri to, in his words, "stand up our next multibillion dollar business." The motivation came from two directions simultaneously: customers telling ServiceNow to take data seriously, and the company's own recognition that its AI ambitions were structurally dependent on solving the data problem first. As Rewari put it bluntly, "the path to agentic AI heaven goes through some form of data hell."
The "4 Cs" Framework Is the Product Roadmap Investors Need to Understand
Rather than pitching speeds and feeds, Rewari laid out a conceptual architecture that organizes the entire data business around what he calls the 4 Cs: Connect, Control, Context, and Converge. The first two — connecting data across external systems and cleaning it continuously — are handled by Workflow Data Fabric. The third, Context, is an area of heavy current investment centered on a new analytics product line announced recently. The fourth, Converge, is RaptorDB, the company's hybrid transactional and analytical database.
The framework matters because it explains why ServiceNow believes it can sell data products without ever leading with a data pitch. "We are on our way to becoming a data and analytics juggernaut by, initially, and even in the midterm, never really selling directly to data and analytics teams," Rewari said. The sales motion is entirely outcome-driven — offering existing ServiceNow platform owners workflows that run ten times faster, or AI agents fed by richer, cleaner data — with the underlying data products essentially invisible to the buyer until they are already embedded.
RaptorDB's Converged Architecture Is a Genuine Structural Advantage
The investment case for RaptorDB hinges on a shift in enterprise database architecture that is still underappreciated in the market. Historically, transactional systems like ERP and CRM processed work, and analytical queries were run separately against data warehouses after the data was physically moved. That latency was tolerable when humans reviewed dashboards on a Monday afternoon. It is not tolerable when millions of AI agents need real-time data to make decisions continuously.
RaptorDB allows both operational and analytical workloads to run on the same database simultaneously, eliminating the latency introduced by moving data. Rewari was direct about the competitive landscape: "Can you think of which — no one else has it, right, at our scale." ServiceNow has also opened RaptorDB to direct querying by third-party tools like Tableau and Power BI, removing the need for customers to maintain separate data pipelines into Snowflake or BigQuery. The company calls this Live Connect. A companion capability, Live Archive, allows customers to tier data by cost within Raptor itself, again eliminating the need for external backup pipelines. Rewari's framing is that both features effectively "self-fund" because of the pipeline costs they eliminate.
Zero Copy and the "Knowledge Gravity" Bet Against the Industry
Perhaps the most strategically important positioning articulated at the conference is ServiceNow's explicit rejection of the data gravity thesis that dominated the cloud data warehouse era. Where Snowflake, Databricks, and others competed to become the destination for enterprise data, ServiceNow is betting on what Rewari calls "knowledge gravity" — the ability to derive insight and drive action from data regardless of where it physically lives.
Through Workflow Data Fabric's zero-copy architecture, ServiceNow federates queries out to data sources in place, whether SAP, Snowflake, Databricks, Google BigQuery, or Oracle, without requiring data migration. "We will logically represent it in Raptor. And at the moment of the question, we'll push down the query and federate it to these underlying data warehouses and data lakes. They're happy because we continue to drive data processing consumption there," Rewari explained. This positions ServiceNow as the orchestration and insight layer above the data infrastructure, not a competitor to it — a stance that makes the Snowflake and Databricks partnerships more durable than they might appear.
The Context Engine Is the Most Underappreciated Asset in the Stack
The piece of the data platform that Rewari spent the most energy on — and that investors appear least familiar with — is what ServiceNow is calling the Context Engine. Built on top of the company's existing CMDB Knowledge Graph, which maps IT components to business services and has been accumulating data for over twenty years, the Context Engine now incorporates identity and user data from the Veza acquisition, asset data from the Armis acquisition, semantic-layer business metrics from the recent Pyramid acquisition, and data catalog metadata from the data.world acquisition, which Rewari confirmed was fully integrated and launched at the Knowledge conference in May 2026.
The result is what Rewari describes as "the graph of graphs." Critically, it also includes what he calls a Decision Graph — a structured record of why past decisions were taken, which exceptions were made, and what outcomes followed, drawn from over twenty years and more than ten billion workflows on the ServiceNow platform. "Unless you've been in this business supporting ten billion-plus workflows with trillions of transactions, how are you going to get it," he said, framing it as a moat that is definitionally irreplicable for new entrants.
The practical relevance for AI is direct. Reducing hallucination and bias in AI agents is demonstrably tied to the richness of the context provided to those agents. The Context Engine is ServiceNow's answer to that problem, and Rewari described it as increasingly becoming a prerequisite conversation for customers considering agentic AI deployments.
Analytics: A $100 Billion TAM That Rewari Says Is in "Profound Disruption"
The Pyramid acquisition, completed roughly two to three months before the conference, brings a semantic layer and modern BI capability into the stack. Rewari pushed back firmly on the notion that analytics is a commoditized layer. His argument rests on three structural changes occurring simultaneously: AI agents need the same governed, authoritative business metrics that humans do; the separation between insight and action cannot survive in an agentic world where the same agent must do both; and dashboards are being displaced by conversational interfaces where AI interprets results and triggers workflows automatically.
"Nobody else can do that," Rewari said of the ability to detect risk and remediate within a single platform. He called the current moment "profound disruption in this $100 billion TAM market" and positioned ServiceNow as uniquely placed because it is converging insight and action in one place. He drew an explicit historical parallel to his time at Oracle, where a BI applications business layered on top of PeopleSoft, Siebel, and JD Edwards grew past $1.5 billion in revenue before expanding beyond the installed base — exactly the playbook he says ServiceNow is executing now.
Go-to-Market Is Still Maturing, With a Key Decision Ahead
On go-to-market, Rewari was candid about where the business stands. Today, core account executives handle initial conversations and pull in data and analytics specialists as needed. But Rewari flagged that the discussion about whether to stand up a fully dedicated Data and Analytics sales force — separate from the specialist model — is actively on the table for the second half of 2026. Given that Rewari described this as "one of the fastest-growing businesses ever in ServiceNow's history, within a company that has already broken past $5 billion, $10 billion, now $15 billion, faster than anyone else," the go-to-market infrastructure question is not trivial.
On customer adoption sequencing, Rewari noted that Workflow Data Fabric tends to come first, largely because ServiceNow is already present in 95% of the Fortune 500 and many customers are already using integration capabilities that technically make them Workflow Data Fabric customers. The upsell is then a tier upgrade to enable zero-copy federation. RaptorDB uptake has been led by large workload customers but is expected to broaden with the new Live Connect and Live Perform capabilities. Analytics through Pyramid is the newest and least penetrated product.
The Ultimate Moat Argument: Architectural Purity Over Twenty Years
When pressed on what is truly durable in the data business, Rewari gave a layered answer — the converged database, zero-copy federation, and the CMDB accumulated over two decades — but was clear that none of those rank first. "Neither of these are what I would put as number one. Number one is the fact that all of these gems are in a single platform. Single data model, single security model, unified user experience for everyone. No one else has that." He traced it directly to founder Fred Luddy's original architectural discipline, quoting Archimedes: "Give me a lever long enough, I will lift the moon."
For investors, the practical translation is lower total cost of ownership, higher accuracy, a single skills base across IT and line-of-business deployments, and a unified security model that eliminates the need for stitching products together. The customers who already use multiple ServiceNow products across ITSM and HR, Rewari noted, are the ones who feel this most acutely — and they are both the easiest upsell target and the strongest validators of the thesis. As he put it, at ServiceNow's Knowledge conference, "you just feel the love."