Coralogix raises $200 million at $1.6 billion valuation as AI drives data surge
Observability company says explosion in telemetry data is accelerating demand, not replacing its core market.
Coralogix has raised $200 million in a Series F funding round, valuing the company at $1.6 billion, a 60% increase from its previous valuation of just over $1 billion. The round was co-led by CPPIB, Greenfield Partners and Advent, with participation from Brighton Park Capital, bringing total funding in Coralogix to $550 million. Existing investors also participated, including Red Dot, StageOne, Aleph, OG Venture Partners, and NeeView Capital.
A small portion of the round, less than 10%, was used in a secondary transaction to allow long-time investors to sell shares, while the majority of the capital will go to the company’s balance sheet.
In a conversation with Calcalist, CEO Ariel Assaraf said Coralogix is now operating at an annual revenue run rate of $150-$200 million, reflecting roughly 60% growth since its previous funding round, with tens of millions of dollars in new revenue added each quarter.
Assaraf addressed the impact of artificial intelligence on the market. “While early concerns suggested AI tools could replace parts of the company’s business, the opposite has occurred: demand has increased significantly due to the explosion in data volumes generated by modern systems,” said Assaraf.
He added that organizations are now reassessing their infrastructure on shorter cycles, and that while development speed was once the main differentiator, today it is relatively easy to build new features. As a result, foundational infrastructure and platform resilience have become the key determinants of competitiveness in the AI era.
Coralogix currently employs around 300 people in Israel and 300 in the United States, alongside offices in London and sales operations in India, Asia, and South America.
Commenting on the labor market, Assaraf said recent waves of layoffs in the industry are temporary adjustments, arguing that demand for engineers will ultimately increase as AI tools improve productivity and expand the scope of technical work.
He also noted that currency fluctuations affect Israel-based companies, saying a stronger dollar would enable greater investment capacity. Despite this, Coralogix continues hiring in Israel and has not reduced headcount, even though costs are higher compared to many global markets, with the exception of the United States.
The current expansion comes amid structural changes in the observability market, where AI-driven applications generate telemetry data at volumes and complexity that exceed the capacity of traditional monitoring platforms built for static workloads and sampled data.
Legacy monitoring tools often incur high costs while leaving visibility gaps for engineering teams. Coralogix’s architecture, by contrast, is designed for real-time streaming analytics, open data formats, and customer-controlled storage without data sampling, enabling AI systems and agents to analyze and manage complex production environments.
Today, many observability workflows rely on manual investigation through dashboards and alerts. Increasingly, however, AI systems are taking over initial triage and surfacing insights before human intervention is required.
To support this shift, the platform integrates “Olly,” a built-in AI agent, alongside MCP and CLI interfaces that allow teams to transition from manual operations to more autonomous monitoring on the same underlying data infrastructure.
The company serves more than 5,000 global customers, including IBM, Tradeweb, and JFrog, and processes petabytes of production data daily across eight regions. It also serves public-sector clients in Israel and has passed qualification processes for U.S. government entities, including the U.S. Department of Education, giving it access to large dedicated procurement budgets.
Coralogix intends to use the new funding to accelerate growth in three key areas: expanding AI-driven observability capabilities using autonomous agents, scaling its Data Lake architecture for long-term data processing at enterprise scale, and broadening adoption among large enterprises in fintech, cybersecurity, and cloud infrastructure as they transition to AI-native systems.
