The Modern Data Company
Turning Data into a Business Growth Engine

Enterprise datasets are too often built as technical instruments for engineers, not as tools for decision-makers. Locked away in mainframes and data lakes, they remain buried in backend systems and out of reach for the business users who need them most.

That gap is what The Modern Data Company set out to close.

Its data operating system, DataOS, is built to give decision-makers direct access to data without relying on technical teams. Instead of raw tables and complex pipelines, business users can access data packaged as governed, contextualized data products they can trust and act on.

“We wanted every data product to be dependable on its own, carrying governance and context so teams don’t need to worry about where it runs or how it’s managed,” says Srujan Akula, co-founder and CEO.

That ease of use comes from a structural shift in how DataOS handles information. Rather than leaving it as raw feeds, the platform embeds lineage, semantics and context into every data product, giving data a shape that business teams and even AI systems can immediately understand.

Models working off raw tables often return results with only an estimated 55 percent accuracy, while the same models operating on DataOS products reach 90 to 95 percent accuracy. For enterprises experimenting with AI, that accuracy shift means moving from proofs of concept to production-ready solutions with far greater speed and confidence.

We wanted every data product to be dependable on its own, carrying governance and context so teams don’t need to worry about where it runs or how it’s managed

The ease of use for business teams comes from automation at the core of DataOS. AI and machine learning scan across sources to map data copies, joins, semantics and costs. Missing metadata is filled automatically, sensitivity is tagged, and persona-based access is applied in real time. From there, governed products are delivered in the formats business teams already use, whether through APIs, GraphQL or BI dashboards. The same layer can power AI agents, automate workflows or fuel lightweight applications that once took months of engineering effort, now happen in days.

That dependability translates into speed. Companies using DataOS can stand up business-ready data products in as little as six weeks. Instead of spending a year or more building pipelines and stitching systems together before a single result can be trusted, they move quickly from setup to value. Because the system overlays existing infrastructure rather than replacing it, this acceleration comes without the disruption of ripping out legacy investments.

One global enterprise generating more than $30 billion in revenue shows the impact clearly. The company had long struggled to unify ERP, CRM and mainframe data. Building a single dashboard took months, and trust in the outputs was low. Six weeks after adopting DataOS, production-ready products were feeding twenty applications. Governed APIs and next-best-action workflows were instantly available, and for the first time, the business could run AI experiments on enterprise data with full confidence in the results.

What Modern has achieved in data follows the same pattern that has defined the biggest technology shifts of the last two decades: scale comes when complexity is stripped away and usability is put in the hands of end users. When iOS delivered intuitive interfaces, the mobile market exploded. When Docker packaged application dependencies into containers, software development accelerated. DataOS brings that same principle to data, turning it into self-contained products that are portable across environments and ready for use at the point of decision.

For The Modern Data Company, success comes from making data practical and accessible. DataOS reduces complexity so enterprises can work with information as easily as any other business tool. That simplicity does more than speed up insights; it creates a foundation where AI, automation and everyday decisions can operate on the same trusted layer. With the right operating system, data becomes intuitive to use and powerful enough to shape outcomes across the business.