Unified data operations startup Matia Inc. wants to give enterprises a better way to manage their data pipelines at scale after raising $21 million in an early-stage A round of funding.

Red Dot Capital led the Series A round, which saw participation from existing backers such as Leaders Fund, Secret Chord Ventures, Cerca Partners, Caffeinated Capital and VelocityX, plus angel investors including Karim Atiyeh of Ramp Network Inc. and Alex Pham of Toyota Motor Corp. To date, Matia has now raised more than $31 million in funding.

Matia is the creator of a unified DataOps platform built on Amazon Web Services that’s designed to consolidate modern data infrastructure stacks into a single interface. It does this by combining data extract/transact/load processes with reverse ETL, data observability and a data catalog, helping teams to reduce tool bloat and speed up their data workflows.

The platform is able to replicate data in real time from more than 100 sources, including popular databases, software-as-a-service platforms and application programming interfaces, to data warehouse platforms such as Snowflake, Databricks and BigQuery. Its reverse ETL capability means it can activate this information by pushing insights from the data warehouse back into operational SaaS tools used by business teams. With its data observability suite, it offers proactive monitoring of data quality, with alerts for any issues such as data pipeline failures.

Matia says teams will benefit from having all of their data operations visible through a single pane of glass, replacing the need to manage multiple tools for ingestion, monitoring and cataloging. Because it can detect data anomalies and errors immediately upon ingestion, it helps to prevent bad or inaccurate data from reaching downstream applications, while its support for parallel synchronization helps it to reduce data pipeline syncing times by up to eight times.

With today’s funding, Matia said, it intends to build upon this foundation with the development of a new artificial intelligence-powered data engineer. It’s essentially an AI agent that’s designed to automatically create data pipelines, detect anomalies and perform impact analysis, among other data management tasks.

Matia co-founder and Chief Executive Benjamin Segal said it’s time for data engineering to enter the AI era, because AI itself requires vast amounts of trusted data and system-wide context. And the best way to provide that is to automate it, he believes. “Matia delivers an AI-ready data layer in one unified platform, replacing fragmented point solutions that lack context,” he explained.

By consolidating all of their data tools into Matia’s unified platform, instead of maintaining separate ingestion, observability and activation systems, customers have reduced their total cost of ownership by about 78% on average, the company said.

Danielle Ardon Baratz of Red Dot Capital said Matia is redefining the data stack for AI workloads. “It stands out by consolidating critical data functions into a single platform that actually reduces operational overhead,” she said.

Segal said Matia has gained strong momentum over the last year, growing its revenue by more than 10 times after winning a deluge of new customers. They include the digital payments firm Ramp, compliance automation startup Drata Inc., freelancer-focused business management platform HoneyBook Inc. and Lemonade Insurance Co.

“We’re seeing a clear shift in how teams think about their data infrastructure,” Segal said of that growth. “As companies scale, they want fewer tools, more shared context and systems that hold up under production demands.”

Image: SiliconANGLE/Nano Banana