Starburst names Moveworks CFO veteran to steer agentic data push

Kerman Lau joins Starburst as CFO, bringing scale-up experience from the ServiceNow-acquired AI platform Moveworks.

By Disrupts Editorial Team Sat, 31 October 2026 AI level 2 of 5

AI level 2 of 5: drafted by our AI editorial assistant from the company's announcement; fact-checked, edited and signed off by Mark Walker, Editorial Director. What the levels mean

A bright, clean data center aisle extends into the distance, lined on both sides by white server cabinets with black handles and glowing blue and green indicator lights, illuminated by rectangular overhead lights.

Starburst, the enterprise data-federation platform built on open-source Trino and Apache Iceberg, has appointed Kerman Lau as its new Chief Financial Officer. Lau joins from Moveworks, the AI-powered employee-support platform acquired by ServiceNow earlier this year, where he steered the company's finances through a period of rapid headcount and revenue growth that culminated in the deal. The hire signals that Starburst is positioning itself for a significant scaling event as enterprise demand for governed, distributed data access accelerates alongside the rise of agentic AI workloads.

Lau brings more than 25 years of finance leadership across high-growth software businesses. His appointment sits at the intersection of two macro-level shifts: the structural move away from monolithic data warehouses toward federated architectures, and the proliferation of AI agents that require reliable, contextualised data access rather than a single consolidated lake.

The agentic data bottleneck

The strategic logic behind the hire is rooted in a specific technical and commercial problem. As enterprises deploy AI agents to automate workflows, those agents need to query data held across on-premises systems, multiple cloud providers, and hybrid architectures simultaneously. Consolidating that data into one platform first is expensive and slow; Starburst's pitch is that its federated query layer removes the bottleneck without forcing migration. Justin Borgman, Starburst's co-founder and CEO, framed the opportunity plainly: "Data becomes the foundation for enterprise AI and we need to invest aggressively in the opportunities that matter while building the financial discipline needed to scale."

Lau echoed the strategic positioning: "Starburst already gives people high-performance, governed access to their data. Agentic workloads need the same things, plus business context a human naturally brings to every query. That's exactly what we're building and I believe Starburst is incredibly well positioned to be the gateway for any workload, human or agentic, to reach the data it needs."

Convergence capital and the governed-data race

The appointment warrants attention beyond the routine CFO announcement precisely because of where Starburst sits in the enterprise AI stack. The company's federated model competes with a cohort of well-capitalised incumbents and challengers, including Databricks, Snowflake, and Google's BigQuery Omni, all of which are simultaneously expanding into governance and agentic orchestration. A seasoned CFO with a demonstrable acquisition exit on his record is the kind of hire a board makes when it is either preparing for an IPO runway or positioning the company as an attractive acquisition target in a consolidating market.

The broader capital landscape reinforces the timing. Enterprise AI infrastructure has attracted sustained investment from both strategic and financial buyers throughout 2025 and 2026, with platform businesses that sit between raw compute and application layers commanding particular attention from growth equity and late-stage venture. Starburst's open-standards architecture, built to avoid vendor lock-in, is a differentiator in procurement conversations with large enterprises wary of ceding data-layer control to hyperscalers.

For cross-sector investors tracking the AI infrastructure buildout, the governed-data category is worth watching as a second-order enabler. Sectors from financial services to pharmaceuticals to defence procurement are deploying AI agents over distributed, regulated data estates. The ability to federate query access without centralising sensitive records is not merely a convenience but, in regulated industries, a compliance necessity. Platforms that solve that problem at scale are likely to sit at the centre of enterprise AI capital flows for the next several years. Lau's mandate at Starburst is, in effect, to convert that structural tailwind into a financeable growth story.