Microsoft has acquired AI-based data engineering firm Osmos for an undisclosed sum, as part of its effort to reduce data engineering friction inside Fabric, its unified data and analytics offering, as enterprises continue to push analytics and AI projects into production.

Osmos’ technology, which applies agentic AI to turn raw data into analytics and AI-ready assets in OneLake, will help customers bypass the common challenges most enterprises face — spending more time around data preparation rather than analysis, Bogdan Crivat, corporate VP of Azure Data Analytics, wrote in a blog post.

In fact, Roy Hasson, senior director of product at Microsoft, in a separate social media post, pointed out that the Seattle-headquartered startup had launched their AI data wrangler and AI data engineering agents on Microsoft Fabric as a native app almost two years ago, and they became quite popular.

“We quickly realized that customers loved using Osmos on top of Fabric Spark, and it reduced their dev and maintenance efforts by >50%,” Hasson wrote.

The startup, before the acquisition, offered Osmos Data Agents for Microsoft Fabric, Osmos Data Agents for Databricks, and Osmos AI-Assist Suite (Uploaders, Pipelines, Datasets), which the company describes as a collection of AI-powered data ingestion and engineering tools that automate the process of bringing external, messy data into operational systems with minimal manual effort or coding.

What the Osmos deal means for enterprises

While Microsoft is yet to divulge more details about the product roadmap for integrating Osmos’ technology in Fabric, analysts say that the integration is likely to help both CIOs and development teams.

For CIOs, the benefit would revolve around operational efficiency and faster time-to-value for analytics and AI initiatives, especially in environments constrained by data engineering talent and budget, said Robert Kramer, principal analyst at Moor Insights and Strategy.

Another upside of the acquisition for CIOs, according to Stephanie Walter, practice leader of the AI stack at HyperFRAME Research, is enabling data engineering automation that is governed, reversible, and auditable.

“As AI moves from experimentation to enterprise scale, this level of controlled automation becomes essential for maintaining reliability, compliance, and trust,” Walter said.

However, Kramer, in contrast to Walter, cautioned that enterprises’ dependence on Osmos’ technology for data engineering inside Fabric may increase platform dependence, raising governance and risk questions about certifying agentic pipelines, auditing and rolling back changes, and aligning autonomous data engineering with regulatory and compliance expectations.

Reducing repetitive engineering work for developers

For developers, though, Kramer pointed out, the acquisition has the potential to improve productivity by reducing repetitive and low-value engineering work around messy data. 

“Tasks such as data wrangling, mapping inconsistent external feeds, pipeline scaffolding, and boilerplate Spark-style transformation code could be generated by agents rather than hand-built, allowing engineers to focus on architecture, performance, data quality, and guardrail design,” Kramer said. 

“The development lifecycle could tilt toward reviewing, testing, and hardening AI-generated pipelines and transformations, with observability, approval workflows, and reversibility becoming core design requirements,” Kramer added.

Complementing recent Fabric enhancements

Analysts also view Osmos’ acquisition as complementing recent Fabric enhancements, including the introduction of Fabric IQ.

“As Fabric expands with IQ, new databases, and deeper OneLake interoperability, the limiting factor shifts from data access to data readiness. Osmos addresses that gap by automating ingestion, transformation, and schema evolution directly within the Fabric environment,” Walter said.

“In the context of Fabric IQ, Osmos helps ensure that the data feeding the semantic and reasoning layers remains continuously curated and stable as upstream sources change. Semantic systems only work when the underlying data is consistent and explainable, and Osmos is designed to reduce the operational friction that otherwise undermines those efforts,” Walter added.

But what about Osmos’ products and customers?

However, it is not all good tidings for existing Osmos customers as the company is winding down three offerings — Osmos Data Agents for Microsoft Fabric, Osmos Data Agents for Databricks, and Osmos AI-Assist Suite — as standalone products in January itself. This means that Osmos’ technology will only currently live inside Fabric, and customers who were users of the Databricks offering and the AI Suite will have to look at alternatives or find a way to work with Microsoft’s offerings.