Having moved to Silicon Valley, Australian big data / AI company Zetaris is at the centre of solving one of the biggest bottlenecks within the most significant shift in our lifetime, targeting a billion dollar plus exit in the next 1-2 years.

In February 2026, the release of new AI tools wiped over one trillion dollars off software company valuations – now known as the ‘SaaS-pocalypse’. In the same month, however, over $250 billion in new capital flowed into venture capital, with 83% of this going to just three major AI companies.

Whether current AI investments are a bubble or not, the real-world shift is happening. CEOs are under enormous pressure to implement AI. But there is a bottleneck: the data is not ready.

The issue is that enterprise data is separated into siloes – different servers, the cloud, edge devices – which makes it impossible for AI tools to access it all. But if AI can only see part of the data, it cannot work reliably. Existing data infrastructure was never built with AI in mind. 

Australian deep tech company Zetaris has solved this problem. Their technology connects to the data where it is, without needing to move anything.

Zetaris has embedded itself in the tech stacks of some of the world’s largest data infrastructure providers and is now gaining steep traction, winning clients off US data giants Snowflake and Databricks.

“We are building the ‘plumbing’ for AI – the data infrastructure which AI tools need to run. We don’t care whether ChatGPT or Claude are around in three years from now – because we are providing a basic service that is needed by any company that wants to access the enormous productivity gains offered by AI.” Vinay Samuel, Zetaris Founder and CEO.

The Problem Nobody Talks About and the Solution Nobody Else Has Built

The promise of AI is real – The problem is in the data

Every CEO on the planet is under pressure to implement AI. The technology itself is ready, but the moment they try to turn it on inside a large organisation, they hit a wall.

Enterprise data is not stored in one place. It lives across dozens of disconnected systems, built up over decades, spread across different departments, in different formats, sometimes in different countries. If AI cannot access all of a company’s data, it generates poor responses – garbage in, garbage out. For a bank, a hospital, a telco or a government agency, that is simply not acceptable.

A recent example is Walmart. In October 2025, Walmart and OpenAI launched Instant Checkout – allowing customers to shop directly inside ChatGPT. Five months later, Walmart pulled the plug noting conversion rates were three times lower than on their website. The problem was not the AI, it was the data – customers reported wrong stock levels, inaccurate delivery times, outdated prices as the AI struggled with the distributed and real-time nature of the data.

The conventional “fix” for companies has been to centralise everything. Copy all the data into a new platform and build AI on top – services offered by data giants Databricks and Snowflake.  On paper, this makes sense, but as AI matures this solution becomes close to impossible.

Centralisation projects for large companies take 6 -18 months minimum and can cost millions a week. While the business is trying to clean and migrate data, the business itself is changing – meaning the work is often obsolete before it is finished.

The result is that over 80% of AI projects fail – not because the AI does not work, but primarily because the data is not ready for it.

Zetaris moves the query, not the data.

Instead of pulling an enterprise’s data into a central platform, Zetaris sends the query to wherever the data already lives – simultaneously, across every source – and joins the answers in real time. This means no data migration, no data copying and no months-long project.

Where Databricks and Snowflake require data to come to them, Zetaris goes to the data. This allows companies to be ready for AI now, without doing anything.

A Strategy Built to Scale and the Traction to Prove It

Zetaris has made the deliberate decision to embed itself in the technology stacks of the world’s largest data infrastructure companies. Rather than build a direct sales force from scratch, they let those partners carry it to their thousands of enterprise clients.

Hitachi Vantara: fully commercialised and selling

Hitachi Vantara is one of the world’s largest enterprise data storage companies. Today, Zetaris is embedded inside Hitachi’s flagship AI product – the Hitachi AI Data Hub – one of three pillar products going to market globally. Together they give enterprise customers AI-readiness, without sending anything to the cloud.

Zetaris Founder Vinay Samuel with Hitachi Vantara Senior VP, Jeb Horton (Credit Hitachi)

The Hitachi partnership has already yielded a million dollar plus ARR contract and a direct pipeline in the tens of millions – with just three dedicated salespeople. Hitachi is now in advanced discussions to expand this to their full enterprise salesforce of 300.

Hitachi clients are also now building AI-powered data products for its clients, using the Zetaris platform. The first live development of which is already operational. Each platform unit supports approximately three end customers, priced at $1.7 million to Zetaris. With 900 potential adopters under only the initial Hitachi client, they represent a potential $500+ million opportunity – from only the first Hitachi client.

One of the most compelling proof points in the Zetaris story is how the Hitachi validation now unlocks the further partnerships. What took 18 months with Hitachi is taking as little as 3-6 months with the world’s largest enterprise networking companies, data centre operators and enterprise software companies – each with tens of thousands of enterprise clients across the globe.

What comes next and what it could be worth

The same market moment that punished SaaS companies has created a clear and immediate tailwind for Zetaris. There is now a clear industry shift as AI projects are being recognised as data projects first.

Multinationals are now coming directly to Zetaris. Some of the largest telcos in the world, already invested in companies like Databricks and Snowflake, are reporting the “fix” is not working for real-time, edge AI use cases, and they need a solution.

Databricks raised its latest round at a $134 billion valuation, generating over $5.4 billion in annualised revenue and growing at 65% year on year.

Snowflake, its closest rival, carries a market capitalisation of approximately $56 billion.

Neither can do what Zetaris does. For Databricks or Snowflake to build what Zetaris has built, they would have to abandon their centralised cloud models that made them multi-billion dollar companies.

Zetaris is in the early stages of what could become a defining position in enterprise AI infrastructure. Founder and CEO Vinay Samuel has held senior roles at leading data‑platform companies including Teradata, Netezza, Greenplum and Vertica, several of which achieved multi‑billion‑dollar exits via IPO or acquisition, and two further successful exits.

He is supported by high-profile US investors like Robert Herjavec, who have built and sold multiple category-defining technology businesses. The technical bench is equally strong, with CTO Michael Hay drawing on senior leadership roles at Hitachi Vantara and Teradata.

Zetaris is one of a very small number of businesses in a market where the companies solving the data problem are the ones attracting billion-dollar valuations.

“Sometimes I am pinching myself – because we are writing a bit of history here. From an Aussie tech startup 10 years ago we are now sitting here in Silicon Valley, at the centre of an industrial revolution. It’s definitely an exciting time to be on this journey.”
Vinay Samuel, Zetaris Founder and CEO.