Precisely and Matillion speed data modernisation and AI readiness

Precisely and Matillion have agreed on a new OEM partnership. It will see Matillion’s cloud-native Extract-Transform-Load (ELT) capabilities embedded into the Precisely Data Integrity Suite. It gives customers a single suite of tools that allows them to accelerate the modernisation of their data environments. More importantly, it will speed up the transformation of data for use in AI.

Ulf Viney, Executive Vice President of Engineering, Support & Operations at Precisely, said, “AI ambition only delivers ROI when the data behind it is modern, scalable, and trustworthy.

“By embedding cloud-native ETL directly into the Data Integrity Suite, we’re eliminating fragmentation and giving organizations a unified foundation to move, prepare, and trust their data, accelerating their path to Agentic-Ready Data.”

How does this deal accelerate data transformation?

One of the core processes in data transformation is ETL. Systems extract data from source locations, often with different attributes and object names. Then they transform the data so it becomes part of a unified set. As part of that process, the transformation corrects and enriches the data based on business rules. The result is a higher quality and consistent data set.

Once systems transform the data, they load it into a new target system. That makes it the source of truth for new applications. Users can query it, use it for complex analysis, and feed decision-making systems. Increasingly, teams also use that data to support new AI-driven applications.

However, research from Precisely and the Drexel University LeBow College of Business shows a problem. The recent Precisely 2026 State of Data Integrity and AI Readiness report (registration required) shows that organisations are concerned about their data integrity status. This is impacting AI projects and making it hard for organisations to show ROI from their investments.

Embedding Matillion ETL creates a smoother workflow

Embedding the Matillion ETL into the Data Integrity Suite lets customers build automated pipelines to manage their data. This ability lets them create proven, trusted, repeatable, and scalable processes.

These automated pipelines also let data teams build self-service options for users. Users can drag and drop data from different sources. Enrichment is then assigned to that data using other drop-down boxes, giving users control over the level and type of enrichment.

Another benefit: many customers use multiple clouds. That means data must be pulled from different sources, which often require different tools. Matillion ETL is a cloud-native solution. It runs in the cloud and accesses data across any cloud storage service.

Among the benefits that Precisely says this partnership will deliver are:

• Low-code, cloud-native ETL/ELT for rapid pipeline development
• Scalable data transformation across hybrid and multi-cloud environments
• Faster time-to-insight for analytics and reporting
• Trusted data foundations for AI and advanced decision-making
• Reduced complexity through unified integration workflows

Enterprise Times: What does this mean?

Many of the challenges that organisations struggle with today are nothing new. They have been around for decades. They are often still using multiple tool sets and doing processes such as ETL manually. Additionally, the volume of data they are working with continues to grow and become more complex.

The target usage for the data from advanced analytics to decision-making systems and AI continues to evolve. That means pulling data from a wider variety of sources and being able to carry out deeper enrichment of the data. Without this, the data will deliver mediocre solutions that will fall short of the demands from the business teams.

To ease things for customers, Precisely has been investing heavily in data sets for enrichment and adding AI capabilities. Now it is adding more traditional tools into the Data Integrity Suite with Matillion ETL. For customers, this will enable them to speed up data transformation and create greater automation.

The question now is what will Precisely add next?

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