Hysata

Hysata provides a cloud‑native data lake platform that combines high‑throughput object storage with a searchable metadata index and serverless transformation pipelines. The service offers a unified API for ingest, catalog, and query of petabyte‑scale unstructured datasets, along with native compute connectors and enterprise‑grade security controls, enabling AI and analytics teams to process data in place while minimizing storage costs.

Traction 10/10

Wollongong, Australia · HQ

Founded 202111010K+ followers

Artificial Intelligence
Data & Analytics
Clean Technology
Energy
Enterprise Software
Hardware
New Materials

Updated 5 months ago

Funding

Raised to date

$111MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

1 founder

Paul Barrett

CEO

Product

Problem

Enterprises and AI developers struggle to store and retrieve massive, unstructured datasets quickly and cost‑effectively, limiting the scalability of machine‑learning workloads and data‑driven applications.

Solution

Hysata offers a cloud‑native data lake platform that combines high‑throughput object storage with a searchable metadata index and built‑in data transformation pipelines. The service abstracts underlying storage infrastructure, providing a unified API for ingest, catalog, and query across petabyte‑scale datasets. Integrated compute connectors enable direct processing of data in place, reducing data movement and latency. Hysata’s platform also includes role‑based access controls, audit logging, and compliance features to meet enterprise security requirements.

Target Audience

Target customers are AI research teams, data engineering groups, and large enterprises that need to manage and process large volumes of unstructured data for machine‑learning and analytics pipelines.

Features

Scalable object storage optimized for high‑throughput AI and analytics workloads
Automatic metadata extraction and searchable catalog for fast data discovery
Serverless data transformation pipelines with support for common ML formats (e.g., TFRecord, Parquet)
Direct compute integration via native connectors for popular frameworks (Spark, Dask, TensorFlow)
Fine‑grained access control and audit logging to satisfy security and compliance standards
Pay‑as‑you‑go pricing model with cost‑optimization tools for storage tiering