Australia’s AI race just got a serious new whale - Databricks is looking to invest half a billion with a Sydney Head Office

are coming!! 

Databricks — the 13-year-old AI and data giant valued at roughly US$134 billion — is preparing a major expansion into Australia under the leadership of Adam Beavis.

And they are not coming quietly.

Fresh off a US$5 billion capital raise backed by investors including Andreessen Horowitz, Macquarie Capital, Australian family offices and sovereign wealth funds including Future Fund, Databricks is planning to invest approximately A$416 million into its Australian growth over the next three years.

The company is reportedly looking at a new 2,000 square metre Sydney headquarters that could house up to 400 staff and serve as its Australia and New Zealand hub.

This is more than just another tech company opening an office.

It’s a signal that Australia is becoming strategically important in the global AI economy.

So what does Databricks actually do?

Databricks helps organisations unify fragmented data spread across departments, systems and cloud environments into what it calls a “lakehouse” architecture. On top of that sits an AI conversational interface called Genie, allowing employees to ask complex business questions in plain English and receive detailed insights from enterprise-wide data.

In simple terms:

It turns disconnected data into usable intelligence.

Why is this resonating?

Because many organisations are facing the same problem:

• AI ambition

• Massive amounts of data

• But legacy systems, governance concerns and skills shortages preventing execution

As Beavis noted, many enterprises are now moving from AI experimentation to measurable business impact.

And Databricks is betting heavily that Australia will be part of that shift.

Its Australian customer base already includes:

• Atlassian

• National Australia Bank

• Telstra

• Airwallex

• Seven West Media

Seven West Media is reportedly using the platform to predict viewing habits and better target advertising.

What is particularly interesting is the scale of the talent and education investment.

Databricks plans to train up to 100,000 people across the region through courses, enterprise programs and events. Within a single enterprise customer like NAB, the company says it could train up to 1,000 employees.

This is not just software deployment.

It is ecosystem building.

The company is also rapidly expanding a specialised “field engineering” workforce — technical experts who bridge the gap between AI capability and practical deployment inside organisations.

At the same time, Databricks is supporting a growing Australian partner network that already numbers around 250 partners.

The broader implication?

Australia’s AI battle is shifting from experimentation to infrastructure.

And the competition is intensifying.

Snowflake remains a major competitor globally, but the next few years may determine who becomes the dominant enterprise AI and data platform across Australian corporates and government.

One thing is becoming clear:

The AI gold rush is no longer theoretical.

The whales are coming!!

The power of relationships data and the ability to influence

lisa Harrison wrote a great article on linked in on the power of relationships data and the ability to influence

Data is important to convince people to make a section and influence them to do something - but here’s the thing………..

No matter how much data you have - to influence people - you need to build a relationship - and to build a relationship you need trust and you need to add value .

Love John Maxwell’s comment - leadership 

is about being able to Influence - nothing more nothing less - and leadership or influence without a relationship is pressure you don’t want 

People don’t care how much you know unless they know how much you care - and there’s no better way to show this than giving them a warm introduction to someone you know like and trust.

And to do this easily - #referron is a game changer 

- #Create your digital business card and showcase your superpower 

- #Connect with people and build your Rolodex 

- #Refer people to relevant people in your network that you know like and trust 

- #Track and follow up your activity 

https://www.linkedin.com/in/lisajharrison?utm_source=share_via&utm_content=profile&utm_medium=member_ios

Ideally secures $16m Series A as investors deepen bet on real-time consumer insight

Auckland and Sydney based market research start-up Ideally has raised $16 million at $100m valuation in a Series A round.  Founded by James Donald, Joshua Nuu-Steele and Brendan Cervin, Ideally is targeting a long-standing inefficiency in the research industry: the time and cost required to generate actionable insight. 

Investors 

led by Shearwater Capital, with participation from OIF Ventures, Altered Capital, Icehouse Ventures and Ecliptic VC, as investors increase their exposure to platforms reshaping how companies understand customers.

OIF Ventures, an early backer of Ideally, has maintained its support through the latest round, underscoring conviction in the company’s trajectory and category positioning. The broader syndicate — spanning Australia, New Zealand and global investors — points to ambitions beyond the domestic market.

Investors are effectively backing the emergence of what some describe as “insight infrastructure”: software that embeds customer understanding directly into daily workflows, rather than treating it as a periodic function.

The problem it Solves 

Traditional research processes can take months and cost six-figure sums, typically delivered through external agencies and static reporting. Ideally’s proposition is to collapse that cycle into a continuous, on-demand workflow, enabling teams to test ideas, validate creative and gather feedback in near real time.

Customers

The company has gained traction across more than 250 brands in Asia-Pacific and the United States, embedding its platform across product, marketing and commercial functions.

Among its customers, Treasury Wine Estates has used the platform to reduce product development timelines from six months to under 90 days by incorporating consumer feedback earlier in the process. Burger King is testing limited-time menu items prior to launch, while Google is applying the tool to link user insight more directly to creative development.

Where to from here? 

The investment reflects a broader shift within corporates towards faster, more iterative decision-making as product cycles shorten and competitive pressure increases. Platforms that enable continuous feedback are beginning to displace traditional, episodic research models.

For Ideally, the next phase will focus on scaling enterprise adoption and deepening integration across decision-making processes. The company is aiming to become a default layer in how organisations test, learn and iterate.

If successful, the shift would mark a departure from traditional research models towards a system where insight is continuously generated and immediately applied — reshaping how companies bring products to market and manage risk.