Mantel Group finds agentic AI is now leading customer conversations

Fresh off another AWS partner award, Mantel Group is seeing a shift toward business-case AI implementations.

AI is now moving away from proof-of-concept projects toward business-case implementations on agentic platforms with proper guardrails and controls.

“I think over the last year it's been a genuine shift to productionising workloads,” said Andre Morgan, AWS partner lead, Mantel Group.

The “factory mindset” is guiding adoption and seeing AI being used to replace business processes and accelerate software delivery life cycles (SDLC) with clear customer outcomes

“It's actually achieving some results and benefits now rather than what were some of the discussions about proof of concepts a couple of years ago,” said Morgan, speaking at last week’s AWS Partner Summit in Sydney.

Mantel was named AWS Consulting Partner of the Year for Australia and New Zealand in the 2026 Regional AWS Partner Awards, marking the fourth time the business has received partner recognition.

Mantel’s customers include the health fund nib and Humm group as well as growing cloud adoption across regulated industries such as financial services.

Its focus has been on upskilling engineers to use agentic tools for more onerous parts of the development process. At present, these applications span design, documentation, coding, and automated testing.

for nib, Mantel built an AI-powered image processing pipeline that automatically extracts and pre-populates key fields from member receipt photos submitted through its mobile app, removing manual data entry.

It has achieved 90 percent accuracy on key fields, made half of all claims fully touchless and delivered close to $1 million in manual handling cost savings over 12 months.

“It's a good example of how we can use the technology and the customer’s business knowledge to achieve some pretty significant outcomes. It’s very high accuracy along with high throughput,” he explained.

Internally, Mantel has been on a deliberate up-skilling program to build AI skills and confidence in the technology that can be translated into customer outcomes. The business ran 101-level education across the whole team, regardless of role, and built sandpits and AI gateways for hands-on experimentation.

“We used these environments to demonstrate ‘the art of the possible’ to customers,” Morgan told CRN Australia.

The goal is to foster cross-discipline expertise and allow each area to apply domain knowledge to agentic use cases.

"It's been a really good journey for Mantel because we have experience across cloud, digital, data and cyber. It means that each one of those areas can apply their deep knowledge of that domain and use agentic technology to solve those typical customer challenges,” he explained.

While some engagements are still tech-led, particularly around SDLC acceleration, Mantel is finding that agentic is leading other client conversations. “Both business-driven and tech-driven conversations are now common,” he said.

Enterprise customers have a clearer sense of what they want, but they often need help building the business case and ensuring agentic development environments have appropriate controls.

“With an operating model change, governance and guardrails are as important as the technology itself,” he said.

The adoption of agentic AI has also resulted in a gradual shift from strictly project-based delivery to consultancy and ongoing engagements.

Ongoing support is becoming essential as AI technology moves so rapidly, and engagements need to adapt to reflect the nature of this continuous partnership, he said.

“Customer expectations are driving some of this change,” he said.