Progress Software completes $400m acquisition of Domo AI platform

Progress Software has closed its $400m purchase of Domo's AI and data platform, adding 2,400 business customers and cloud data warehouse partnerships.

A modern, brightly lit control room with rows of empty desks, multiple computer monitors, and a large video wall displaying colorful data visualizations and text.

Progress Software (Nasdaq: PRGS) has completed its acquisition of substantially all assets of Domo's AI and data platform business in a deal valued at $400 million, funded through a mix of cash and its existing revolving credit facility. The Burlington, Massachusetts-based company said Domo's cloud-native platform will be absorbed into its existing data offerings, expanding its capability to help enterprise customers connect, govern and activate data for AI and agentic workloads.

The deal brings more than 2,400 business customers into Progress's base, along with a network of global strategic partners including, the company said, leading cloud data warehouse providers. No specific partner names were disclosed in the release. Progress will provide a fuller account of the financial impact on its third-quarter earnings call, scheduled for 30 September.

The deal

Chief executive Yogesh Gupta framed the rationale around two pillars he described as "context" and "control." "As organisations pursue AI initiatives, the challenge is no longer simply access to AI technology," Gupta said. "It is creating the right context, grounded in trusted data and knowledge, and maintaining the right control through governance, security and oversight."

The acquisition follows an earlier announcement of the terms, meaning the 22 September closing date represents the operational completion rather than the initial agreement. Progress did not disclose the precise split between cash and credit-facility drawdown, nor did it provide guidance on expected revenue contribution or synergy targets ahead of the earnings call.

Market context

The deal reflects a broader consolidation trend in the business intelligence and data platform market, where mid-tier vendors have faced growing pressure from hyperscaler-native analytics services (Microsoft Fabric, Google Looker, AWS QuickSight) and specialised AI data layer startups. Domo, which went public in 2018, had positioned itself as a cloud-first BI and data app platform but struggled to scale against better-capitalised rivals and reported persistent operating losses in recent years.

For Progress, which has historically grown through acquisitions in developer tools and infrastructure software, the Domo deal represents a meaningful step into AI-grounded data governance, a category attracting significant enterprise spending as customers look to operationalise large language model deployments responsibly. Competitors in the data governance and enterprise AI context layer include Collibra, Alation and a number of well-funded startups pursuing similar data-fabric approaches.

Regulatory and governance read-across

Enterprise buyers integrating Domo workloads into Progress's platform will need to consider how the combined offering aligns with data governance obligations under GDPR and, for US federal or regulated-sector customers, FedRAMP and SOC 2 certification requirements. Progress has not stated the certification status of Domo's inherited infrastructure or any remediation timeline, which will be a practical concern for regulated-industry customers evaluating the transition.

The European AI Act's obligations on providers of general-purpose AI systems and data infrastructure tools are also phasing in through 2026 and 2027, adding further compliance weight to how Progress positions the combined platform for its European customer base.

Progress said it expects to give a more complete picture of integration plans, revenue outlook and synergy expectations when it reports third-quarter results on 30 September. Investors and customers will be watching for clarity on product roadmap convergence and any rationalisation of overlapping platform features.