Amazon Quick has launched in Australia in the Sydney Region, with Codex - a data and AI consultancy based out of Queensland - being one of the first local AWS Partners who have deployed it internally to run customer practices.
Amazon's Quick Suite is an agentic tool that answers work-related questions and aims to turn insights into actions in a safe environment. Instead of switching between multiple applications to gather data, find signals and trends, and complete tasks, Amazon Quick Suite brings AI-powered research, business intelligence, and automation into one workspace.
It connects to business data and information resources across internal places like wikis and intranets, applications like Gmail, Google Drive, Office 365, Salesforce, and Slack, AWS services like Amazon S3, and access integrations to connect to 1,000+ apps through MCP.
Pip Gilbert, AWS' head of partner ANZ, said that Codex has gone looking for where team members and customers are losing time in their day, and where an agent could make things a bit simpler.
"The Chief of Staff agents are a great example. They help Codex staff sort through their emails and Slack messages and work out what matters most, based on their own role and priorities," she told techpartner.news.
"Codex is also big on training and enablement. Lots of businesses are rolling out AI, but what really matters is whether their people are adopting it and seeing the value. With Quick now available in Australia, our partners like Codex are helping organisations move from piloting agentic AI to scaling it across the business in a secure manner.
"We're also seeing our partners being able to secure more work to set up data foundations and governance practices, after the initial Quick rollout."
With Codex having built agents for HR, finance, sales and AWS Funding, Gilbert said the company has Flows - a capability within Amazon Quick that lets any user create, customise, and share workflows that automate routine tasks - running funding and business case approvals.
"The bit that really stands out for me is how they've made AI adoption itself into a use case. They've built an onboarding app they can tailor to each customer," she explained.
"It walks people through getting set up, connecting their tools and building their first use cases. And the customer can also see how adoption is tracking along the way."
techpartner.news spoke to Julian Campbell, founder, director and CSO of Codex, about how the AWS Data and AI partner is using the technology, what challenges they've encountered and what use cases are emerging among customers.
techpartner.news: What prompted Codex to adopt Quick internally and what were you hoping it would change about the way your team works?
We don't recommend technology to customers that we haven't pressure-tested ourselves. That's a non-negotiable. When Quick came onto our radar, we saw a platform that could fundamentally change how consulting partners operate. We wanted to reimagine how people access knowledge, make decisions, and get work done.
What we wanted to change was simple: eliminate the friction that slows down smart people. As we scale, the challenge is making sure every person in the business can access the right information at the right time without tapping someone on the shoulder or digging through five different systems. Quick had the potential to become the connective tissue across our entire operation.
techpartner.news: Having now used it yourselves, where has it delivered the most tangible productivity impact?
Knowledge accessibility: We've configured spaces and chat agents aligned to key business topics, functions, and processes. We want our people to get intelligent, contextual answers immediately.
Governance and review workflows: We've deployed flows that use AI to conduct initial reviews and provide feedback before anything lands on an executive's desk for final approval. Senior operators are spending more time with customers and less time buried in internal processes. That shift alone has been worth the investment.
Applications: We rebuilt core parts of our operating system in Quick Apps. As an example, our new HR Hub built in Quick Apps, handles performance assessments, career progression plans, and promotion business cases. This solution is designed, built, deployed and managed by our Chief People Officer. The impact has resulted in a huge time savings for people and partners who work through these processes together. That’s a single example.
techpartner.news: Can you give us a specific example of a task or workflow that previously involved several people or systems that Quick can now help streamline?
As an AWS partner, we have access to hundreds of programs that support customers with co-investment at different stages of their journey. Knowing which funding program to use for a specific use case, then navigating the application and approval process has been a highly administrative exercise requiring deep institutional knowledge. You'd need to find the one person who knew the answer, and if they were busy, you waited.
We've built dedicated spaces loaded with all of the relevant AWS funding information, integrated with chat agents that guide our people through the entire journey. Our people can now identify the right program, completing the application, and navigate the approval workflows with AWS. For a business bringing on new people regularly, this is massive. Day one, a new team member can find the right program and execute without leaning on a senior colleague. This is how we are scaling without losing quality.
techpartner.news: Were there any challenges or limitations you encountered during adoption that customers should know about?
The technology is powerful, but the value you extract is directly proportional to the thinking you put into configuration. This isn't plug-and-play. You need to be deliberate about how you structure your spaces, design your agents, and map flows to real business processes.
The biggest challenge is organisational. You need someone who understands both the business and the platform deeply enough to design the right architecture. Treat it like just another software rollout and you'll get underwhelming results. Treat it as an operating model uplift and the returns are significant.
Change management matters too. People need to trust the AI outputs before they'll change their behaviour. We invested time building that trust, showing people the quality of responses and letting them validate against what they already knew.
techpartner.news: How has using the technology yourselves changed the way Codex approaches AI projects for customers?
When you've lived with a platform and felt the friction of getting configuration wrong and the acceleration of getting it right, you advise customers completely differently.
We're now innovating with Quick to create personalised onboarding experiences. When someone joins Quick, they get a tailored experience based on their role and domain, providing both a general understanding of the platform's capabilities with specific recommendations on how to configure it for use cases relevant to them. That came directly from our own rollout.
More broadly, we've moved from talking about AI in the abstract to showing customers exactly what it looks like in production. We can demonstrate our own spaces, our own flows, our own apps. We're able to share what's already working.
techpartner.news: When you speak to Australian enterprises today, where are they on their AI adoption journey - and what is holding them back from moving beyond experimentation?
Many organisations we are supporting have moved past experimentation and are running AI in production. The real issue is benefits realisation. We don't see enough organisations investing in a robust framework to measure and track the actual business value of what they've deployed.
Here's the thing: more than ever before, inputs and workflows are measurable. With the right thinking, for any use case or solution, you should be able to measure ROI in real-time in production. But that work needs to happen at the use case assessment stage, before anything is designed, built, or deployed. When you force teams to articulate the benefits against operating costs upfront, it sharpens everything that follows.
Benefits realisation is one piece in a long list of governance and change management requirements to make AI adoption successful, but it's the one I see customers getting wrong most often. And it's the thing that's slowing down enterprise-wide acceleration. Without it, you end up with pockets of impressive results that never translate into the organisational confidence needed to scale.
techpartner.news: What do you think is the selling point of Quick for customers? What's the most common question you've received around Quick?
Quick is a genuine enterprise AI platform. It connects to your data, your applications, and your processes regardless of vendor, and gives you the building blocks to create real business solutions without needing a development team.
The most common question we get is: "Where do I start?" We are being brought into engagement by AWS where customers already understand the platform is capable, they just need help identifying the highest-value use case. That's exactly where we focus: find the win that builds momentum.
The second most common question is around trust and security. "Where does my data go?" Quick runs on AWS with enterprise-grade security, your data stays in your control, and it meets the compliance standards Australian enterprises need. That answers the question fast and removes a major blocker.
techpartner.news: Which sorts of customers are showing the most interest in Quick? Any particular use cases you're seeing emerge?
We work across AWS' top commercial industries and the early momentum has been strongest with customers who already have a deep partnership with AWS. These are organisations that have run internal pilots, seen impressive results, and are now translating that into broader organisational rollouts.
Knowledge management and intelligent search is the primary entry point. Getting people to the right answer fast, grounded in their own organisational data. That's the use case that clicks immediately and builds confidence for what comes next.
It's still early days, but the momentum is growing. The customers moving fastest are the ones who come in with an openness to reimagine how work gets done, not a general desire to "do AI." That focus makes all the difference.
.jpg&h=142&w=230&c=1&s=1)
.jpg&h=142&w=230&c=1&s=1)
