Nextdata Provides a Platform for Distributed Data

I previously described data mesh as a cultural and organizational approach to distributed data ownership, access and governance, rather than a product that could be acquired or even a technical architecture that could be built. While that remains true, many data management software providers have adapted their products in recent years to address the four key principles of data mesh: domain-oriented ownership, data as a product, self-serve data infrastructure and federated governance. New data management providers have also emerged with products built around these principles, including Nextdata, which is led by the originator of the data mesh concept.

Nextdata was founded in 2022 by Zhamak Dehghani, three years after she coined the term data mesh while serving as a principal consultant at technology consultancy Thoughtworks. Nextdata was founded with the goal of creating a unified development and operating system for autonomous data products, enabling decentralized teams to develop, manage and share data products. The company raised $12 million in seed funding led by Greycroft and Acrew Capital in late 2023, and the Nextdata OS product was launched in April 2025. As I recently noted, it is clear that many enterprises have identified that they need to improve data management with a view to accelerating strategic artificial intelligence (AI) initiatives, with more than one-half (54%) of participants in ISG’s 2025 Market Lens Data and AI Program Study citing the usability of data for AI applications as a significant data challenge. Nextdata’s pitch is that traditional approaches to data management conducted by centralized IT teams with existing tooling are too slow and cumbersome to be able to cope with the scope and scale required for enterprise AI initiatives. The combination of distributed data ownership and automation delivered by Nextdata OS is designed to simplify data management and facilitate the creation, sharing and management of data products to accelerate AI initiatives.

ISG defines data products as the outcome of data initiatives developed with product thinking and delivered as reusable assets that can be discovered and consumed by others on a self-service basis, together with associated data contracts and feedback options. Many organizations are adopting the concept of data products with a view to ensuring that the outcomes of data projects can be shared and reused for multiple use cases across the business and enable enterprises to streamline and accelerate the delivery of analytics and AI initiatives. Although the creation of data products is not dependent on data ownership being distributed to business domains rather than centralized IT, the two concepts are closely associated. More than one-half of participants in ISG’s Data and AI Program Study have distributed responsibility for at least one data initiative to business units. More than one-quarter (27%) have adopted business unit ownership for data and insights reporting, followed by data science and analytics (22%), data cleaning and deduplication (21%) and AI initiatives (17%).

Nextdata OS is designed to automate the development, management and sharing of data products for consumption by business users and AI agents. Data owners can use Nextdata OS to create data products and code-based data contracts and access policies using their preferred notebooks and tools, while a copilot interface, known as Nexty, enables business users to define data products using natural language. Nextdata OS automatically provisions the required compute and storage resources and generates semantic model definitions, as well as data transformation, access controls and quality controls. The resulting data product can be accessed by data consumers via a search-based user interface or agents via API. Each data product can be accessed as a table, a file, a vector embedding (for retrieval augmented generation) or as a Model Context Protocol (MCP) endpoint. MCP has recently emerged as a key open standard for enabling agentic AI by providing connectivity between agents and the data needed to support automated action execution. Nextdata OS also provides lineage and semantic graph capabilities to enable understanding of data product connections and relationships, while data product owners and administrators have access to performance and health monitoring and management information, including consumption and utilization insights.

I assert that by 2027, more than 3 in 5 enterprises will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to domain-based data ownership. Data management products are also adapting to deliver functionality that enables the production, classification, consumption and management of data products. As I previously explained, the 2024 ISG Buyers Guide for Data Products illustrated that while many software providers offer functionality that could be used to facilitate the development and consumption of data products, fewer have delivered capabilities to view and manage access to data products, monitor data product usage and performance metrics, or develop and manage data contracts. I recommend that any enterprises evaluating platforms to support the development of data products and adoption of data mesh include Nextdata in their assessments.

Regards,

Matt Aslett