Problem
Dimeo Cleaning Services, a leading Australian cleaning company, needed to modernise how it captured and used data from IoT sensors at client sites. Their existing Enterprise Portal provided only hourly updates, limiting real-time visibility into site conditions, inspections, service tickets, and customer sentiment, which impacted responsiveness and operational efficiency.
Moreover, the underlying AWS IoT pipeline had become cost-prohibitive, with high volumes of presence and volumetric sensor data driving up unsustainable operational costs. Dimeo turned to Idea 11 to re-architect a more scalable, cost-efficient solution that could grow with the business.
Solution
Idea 11 conducted a full technical discovery of Dimeo’s AWS IoT environment and Enterprise Portal, resulting in a high-level analytics solution design that enabled near real-time data updates. Aligned with AWS Well-Architected Framework principles, the design specified optimal services for data ingestion, transformation, and presentation, along with architecture diagrams, cost estimates, and reliability considerations. Idea 11 collaborated closely with Dimeo’s internal tech and project teams, as well as their third-party development partner, to implement the solution.
Result
The redesigned IoT pipeline delivered a tenfold reduction in Dimeo’s monthly operating costs and significantly improved system resilience. With near real-time sensor visibility across sites, Dimeo can now make faster operational decisions, enhance tenant satisfaction reporting, and reduce manual overheads.
The solution positions the company for scalable growth and stronger performance in competitive tenders, underpinned by an expert technical approach and seamless collaboration across internal and external teams.
“The project was executed with professionalism, technical excellence, and strong cross-team coordination, ultimately delivering significant operational and financial benefits for Dimeo.”
