Akave raises $6.65M in funding to break big cloud’s grip on AI data storage

Akave thinks the real choke point in AI isn’t models. It’s data. The Austin-based AI infrastructure startup has raised $6.65 million and is entering the cloud storage market with Akave Cloud, a decentralized, S3-compatible platform built for AI and analytics workloads. The pitch is straightforward: give enterprises a way to move large datasets across environments without getting trapped by egress fees or vendor lock-in.

As AI systems grow larger and more data-hungry, storage economics have quietly become a pressure point for many teams. Traditional cloud providers still dominate the market, but their pricing models often make long-term costs hard to predict. Akave is betting that frustration opens the door for a new kind of storage layer.

“Distributed systems improve scale and resiliency by spreading workloads across multiple nodes, but decentralization reduces reliance on any single controlling party, a distinction critical for enterprises deploying AI,” said Stefaan Vervaet, founder and CEO of Akave. “The real challenge is maintaining control over where data lives, how it moves, and how it’s governed across environments. We built Akave Cloud to provide a portable, verifiable storage foundation that enables enterprises to run AI workloads with full data ownership, auditability, and long-term flexibility.”

With $6.65M in Funding, AI Infrastructure Startup Raises to Challenge Traditional Cloud Storage with Compute-Agnostic Platform Built for AI Applications

The company’s approach centers on separating compute from storage. Akave positions its platform as compute-agnostic, meaning customers can run workloads across hyperscalers or newer AI-focused clouds without restructuring their pipelines. The system runs on a dedicated Avalanche Layer 1 blockchain, which the company says provides auditability and programmable access controls alongside standard object storage performance.

Akave Cloud is built to plug into existing data workflows. It supports the S3 API and connects with tools like Snowflake and Apache Iceberg, allowing teams to run analytics and machine learning jobs without moving data into a single vendor’s ecosystem. The platform includes an option to archive data to the Filecoin network, with immutable content IDs attached to each object.

The broader bet is that data sovereignty will become a defining issue for enterprise AI. Many organizations are now asking where their training data sits, who can access it, and how it moves across environments without introducing compliance risk.

“The next generation of AI infrastructure will be defined by portability, transparency, and governance. Akave Cloud demonstrates how decentralized storage, built on a dedicated high-performance Avalanche L1, can enable enterprises to manage data with greater sovereignty while supporting the scale and compliance requirements of modern AI workloads,” said Matias Antonio, Chief Investment Officer of Avalanche Foundation.

Founded in 2024, Akave is backed by Protocol Labs, No Limit Holdings, Blockchange, Lightshift, Blockchain Builders Fund, Big Brain Holdings, Avalanche Foundation, and the Filecoin Foundation. The company says its platform is already in use by organizations working with large, data-intensive pipelines.

Among early customers, Intuizi processes consumer intelligence datasets for marketing analytics, LaserSETI stores high-throughput astronomical observations, and 375ai manages large AI training datasets collected from edge camera devices. Skymapper uses the platform to store data from the telescope and all-sky cameras with cryptographic provenance.

Akave Cloud is now available to enterprises and developers. The company is stepping into a crowded storage market, but it is targeting a narrow and growing pain point: teams running AI workloads that want predictable costs and more control over where their data lives.