At the tail end of 2024, a major infrastructure and civil engineering company operating across Australia and New Zealand, reached out to explore how Inde could support the execution of its AI Chat Solution that was in development.
Initially released to a pilot group of 300 users, the AI Chat Solution offered a simple text-based interaction model. With plans to scale to 7,000 users by February 2025, Inde’s client identified the need to improve both the interface and core functionality before a full organisation-wide rollout.
Having worked with Inde for innovative IT solutions and thought leadership for a number of years, they reached out to understand the team’s AI capabilities and capacity to deliver the solution for the desired February rollout date.
Following the success of the initial scoping and proof of concept, the client immediately signed on to have Inde take over the execution of the solution.
The enhancement and rollout of the Azure AI Chat Solution was delivered through three interconnected projects, each addressing a critical phase of the solution’s lifecycle. Despite tight timeframes and the challenges of the holiday period, Inde and their client worked in close collaboration to move from concept to enterprise-wide adoption in just a few months.
By focusing first on understanding requirements, then rapidly prototyping and deploying, and finally establishing long-term support, Inde ensured that the AI chat solution was not only fit for purpose at launch but also positioned for ongoing innovation and scalability.
This phase began just before the 2024–25 summer break. Although another partner had been involved, the client saw an opportunity for Inde to step in and accelerate progress.
Inde quickly organised and facilitated workshops with key stakeholders, to understand the business needs and technical landscape. The Inde team initially approached the workshop with a low-code platform-based solution in mind, but after deeper discussions around the client’s goals and technical requirements, it became clear that a secure Azure Open AI based approach would offer a better long-term fit. By the next morning, the team had updated the prototype to match this approach – which was met with enthusiastic feedback.
Due to the tight timeline, the team didn’t proceed with a formal options paper. Instead, the workshops themselves became the foundation for design decisions, enabling rapid alignment and fast-tracked delivery. A second statement of work was initiated in mid-January as teams returned from the break.
With stakeholder buy-in and a working prototype in hand, the team moved quickly into rollout.
Key features introduced during this phase included:
To ensure the Azure AI Chat Solution continues to evolve with the client’s needs, Inde established a monthly support service for maintenance, enhancements, and delivery management.
Regular fortnightly meetings were set up to prioritise tasks, track progress, and align with business goals. This phase also included continuous updates based on user feedback, bug fixes, and the development of new features. A backlog of post-production enhancements was created to guide future development in a sprint-based model.
The partnership has since expanded to include new use cases, such as a code review bot that evaluates developer submissions against the client’s coding standards as well as facilitated hackathons with their internal IT team to further explore AI innovation across the business.
“Our focus from day one was on being responsive and adaptable to the client’s needs. We didn’t just want to deliver a product, we wanted to build something usable, intuitive, and ready to scale. Seeing the positive feedback from users has been a real validation of the design thinking and deployment approach our team took.”
The Azure AI Chat Solution rapidly evolved from concept to enterprise-ready solution, thanks to a highly collaborative and agile approach between Inde and their client. This momentum carried through to a successful rollout in early 2025, with strong user adoption driven largely by word of mouth.
The solution’s modular architecture and sprint-based enhancement model position it for long-term scalability and ongoing innovation. This approach enables the client to flexibly integrate a variety of large language models (LLMs) and data sources to meet evolving business needs. As new LLMs become available, they can be quickly assessed and adopted. This flexibility allows different models to be applied according to the persona or specific use case of each AI assistant, ensuring optimal performance across diverse scenarios.
The business’ internal teams have been empowered through training and documentation, while ongoing support from Inde continues to drive new use cases such as a code review bot and upcoming hackathons. With usage steadily increasing and new opportunities emerging, this AI chat solution is quickly becoming a cornerstone of this client’s digital transformation journey.
At Inde, we are committed to delivering technology that drives meaningful customer outcomes. We do not operate our own AI platform as a service. Instead, every AI engagement is co-designed with our customers and deployed within their environments. Our approach is tailored, collaborative, and focused on what works best for each organisation. Please contact us if you would like to discuss how we can help your organisation implement AI.
