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Edelbyte raises $70M at a $500M valuation

Startups1 min read

In brief

Edelbyte, which builds a data analytics platform optimized for AI agents, has raised $70 million across two rounds. Sequoia Capital led the $25 million seed round and Quiet Capital led the $45 million Series A, bringing the company to a $500 million valuation.

  • Data analytics platform optimized for AI agents
  • Manages up to hundreds of petabytes in a single environment
  • Supports vector data alongside standard records
  • Queries data in place without moving it
  • Claims sub-100 ms latency on multi-petabyte datasets

$70M across two rounds

Founded in 2025, Edelbyte has closed a $25 million seed round and a $45 million Series A, raising $70 million in total. Sequoia Capital led the seed round, with Greenoaks and Swish Ventures participating. Quiet Capital led the Series A, joined by QP Ventures, Startpoint Capital and Cerca Partners.

The rounds put the company at a $500 million valuation. Edelbyte said the funding will go toward expanding its customer base and growing its team.

What it does

Edelbyte builds a data analytics platform designed for AI agents. It lets companies store, search and analyze large-scale data, managing up to hundreds of petabytes in a single environment.

Alongside standard data records, the platform supports the vector data used by AI agents. It covers search, business intelligence and graph processing needs within one infrastructure.

A Snowflake and Databricks alternative

Edelbyte positions itself as an alternative to Snowflake and Databricks. Its key claim is that queries can run where the data already lives, without moving it, which aims to cut data transfer and speed up analysis.

Using indexing and various optimization methods, the company says it can query multi-petabyte datasets with sub-100 millisecond latency. Its founders are Avner Aharoni, Evgeney Ryzhyk, Alexander Sloutsky and Yoni Leibowitz.

Why it matters

The data layer for AI agents is attracting fresh investment; this is a good hook to introduce a new challenger to Snowflake and Databricks.

Sources

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