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Matia raises $21M to help enterprises consolidate their data management operations - SiliconANGLE
Matia raises $21M to help enterprises consolidate their data management operations 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."
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Israeli start-up Matia secures $21 million investment to create AI-powered data pipeline platform
The company reported exponential growth in 2025, with ten times as many clients using its data analysis solutions, according to their statistics. The Israeli start-up Matia announced on Tuesday that it raised $21 million in a Series A funding round led by Red Dot Capital, bringing its total capital raised to $31 million. The start-up is currently developing a unified platform for operating data pipelines at scale, and will use the new funding to accelerate product development and go-to-market efforts as demand surges for unified, AI-native data infrastructure. "Matia's platform brings data ingestion, observability, cataloging, and reverse ETL together in a single system designed for reliability and operational clarity," said the company in a statement. Alongside Red Dot Capital, the funding round had existing investors like Leaders Fund, Secret Chord Ventures, Cerca Partners, Caffeinated Capital, and VelocityX, with several angel investors, including Karim Atiyeh (Ramp), Udi Mokady (Cyaberark), Amiram Schchar (Upwind), Alex Pham (Toyota), Raffi Kesten, and Abe Peled. "Data engineering is entering an AI-native era, but AI depends on trusted data, system-wide context, and a developer experience teams can actually work with," said Benjamin Segal, Co-founder and CEO of Matia. "Matia delivers an AI-ready data layer in one unified platform, replacing fragmented point solutions that lack context." Start-up shows ten times growth in last year According to their data, the company has grown exponentially over the last year, with ten times as many customers adopting its platform in 2025. "Today, companies including Ramp, Drata, HoneyBook, and Lemonade rely on Matia to run their data operations," the statement said. "We're seeing a clear shift in how teams think about data infrastructure," Segal added. "As companies scale, they want fewer tools, more shared context, and systems that hold up under real production demands. That's what's driving our growth and why customers are standardizing on Matia." An internal report by Matia found that customers consolidating multiple data tools reduced their total cost of ownership by 78% compared with maintaining separate ingestion, observability, and activation systems. Danielle Ardon Baratz, Partner at Red Dot Capital Partners, said, "The speed of their [Matia] growth and the caliber of their customers show they've hit real product-market-fit, and we're excited to support them as they bring AI-driven automation to data operations." The company assured that its goal with this new investment is to help teams of any size and experience level operate data systems with the same confidence and reliability expected of modern production infrastructure.
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Israeli startup Matia secured $21 million in Series A funding led by Red Dot Capital to develop an AI-powered data engineer that automates pipeline creation and anomaly detection. The company's unified DataOps platform consolidates data management operations, helping customers reduce costs by 78% while growing revenue 10x in the past year.
Israeli startup Matia has closed a $21 million Series A funding round led by Red Dot Capital, bringing its total capital raised to over $31 million
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. The round attracted participation from existing backers including Leaders Fund, Secret Chord Ventures, Cerca Partners, Caffeinated Capital, and VelocityX, alongside angel investors such as Karim Atiyeh from Ramp Network and Alex Pham from Toyota Motor Corp1
. The funding arrives as enterprises increasingly seek to consolidate data management operations and reduce the complexity of managing multiple disparate tools.
Source: Jerusalem Post
Matia plans to use the fresh capital to develop an AI-powered data engineer that will automatically create data pipelines, detect anomalies, and perform impact analysis across data management tasks
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. Co-founder and CEO Benjamin Segal emphasized that data engineering is entering an AI-native era where AI itself requires vast amounts of trusted data and system-wide context. "Matia delivers an AI-ready data layer in one unified platform, replacing fragmented point solutions that lack context," Segal explained1
. This AI-powered data pipeline platform represents a shift toward automation in an industry traditionally reliant on manual configuration and monitoring.
Source: SiliconANGLE
The company's unified DataOps platform, built on Amazon Web Services, consolidates modern data infrastructure stacks into a single interface by combining data ingestion through extract/transform/load processes with reverse ETL, data observability, and a data catalog
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. The platform replicates 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 BigQuery1
. By addressing tool bloat, Matia helps teams reduce the operational overhead of managing separate systems for ingestion, monitoring, and cataloging.Matia's data observability suite offers proactive monitoring of data quality with alerts for issues such as data pipeline failures
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. The platform's ability to detect data anomalies and errors immediately upon ingestion prevents bad or inaccurate data from reaching downstream applications, while its support for parallel synchronization reduces data pipeline syncing times by up to eight times1
. This focus on data quality becomes increasingly critical as organizations rely on accurate information to power AI models and business intelligence systems.Related Stories
By consolidating multiple 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 approximately 78% on average
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. The DataOps platform has gained substantial momentum, with the company reporting that revenue grew more than 10 times over the past year after winning customers including digital payments firm Ramp, compliance automation startup Drata, freelancer-focused business management platform HoneyBook, and Lemonade Insurance1
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.Danielle Ardon Baratz, Partner at Red Dot Capital Partners, noted that Matia is redefining the data stack for AI workloads by consolidating critical data functions into a single platform that reduces operational overhead
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. "The speed of their growth and the caliber of their customers show they've hit real product-market-fit, and we're excited to support them as they bring AI-driven automation to data operations," Baratz added2
. Segal observed a clear shift in how teams approach data infrastructure, noting that as companies scale, they want fewer tools, more shared context, and systems that hold up under production demands1
. This trend suggests that enterprises will continue seeking integrated solutions that can support both traditional analytics and emerging AI workloads without requiring teams to manage fragmented toolchains. The development of Matia's AI agent for automated pipeline creation and ETL management could signal broader industry movement toward autonomous data operations.Summarized by
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