Cutting Manual Work by 40+ Hours a Week
A mid-sized logistics firm wanted to automate customer service but didn’t know how to build an AI team.
The Challenge
A major financial services provider was struggling with inefficiencies in their data processing pipeline. Their analytics team spent over 40 hours a week manually preparing and cleaning datasets for internal reporting. The company had explored automation tools but lacked the right talent to lead implementation.
They turned to AYORA to find an AI automation specialist who could design and integrate an intelligent data pipeline that reduced manual intervention.
Our Solution
AYORA’s recruitment team worked closely with the company’s CTO to define the exact blend of skills needed — combining automation engineering, Python development, and knowledge of financial data systems.
Our vetting process prioritised practical experience in automating workflows using machine learning-based data preparation. Within 12 business days, we delivered a shortlist of pre-qualified candidates with proven track records in building similar solutions.
The Result
The client hired a mid-level AI automation engineer from Melbourne through AYORA. Within two months, the new hire deployed a custom pipeline that reduced manual work by 43 hours per week, improved accuracy by 27%, and freed senior analysts to focus on high-value insights.
The success of this engagement led to additional hires, expanding the client’s AI operations team under AYORA’s ongoing recruitment support.