YepAI exists for one mission: to help e-commerce merchants boost sales, reduce workload, and deliver exceptional customer experiences through intelligent AI agents. To push the boundaries of speed, accuracy, and operational efficiency, we formed a strategic partnership with a PhD research team from RMIT University.
Together, we set out to bridge world-class academic research with real commercial outcomes—building AI that isn’t just theoretically advanced, but practical, profitable, and built specifically for online retailers. The result is a new generation of AI agents engineered to serve the fast-moving needs of e-commerce merchants who rely on speed, precision, and real-time product recommendations to grow their stores.
One of the largest challenges facing e-commerce AI is the substantial computational cost of generating fast and relevant product recommendations. RMIT’s team tackled this head-on, developing lightweight neural networks and highly efficient path-finding algorithms that dramatically reduce processing load.
This breakthrough enables YepAI to intelligently navigate large product catalogues with minimal resource usage—critical for e-commerce merchants on platforms like Shopify, who manage thousands of SKUs and high volumes of shopper enquiries.
Verified internal gains include:
35% faster inference speed, enabling near-instant replies.
28% lower computational costs, improving long-term efficiency.
20% higher recommendation accuracy, driven by optimised product tagging and smarter content matching.
For e-commerce merchants, these improvements unlock a smoother, more personalised shopping experience. YepAI’s AI agent now delivers faster product recommendations, more accurate tagging, and real-time assistance—helping buyers find what they want in seconds and reducing drop-off during high-intent moments.
E-commerce merchants operate in fast, high-pressure environments where every second affects conversion. To meet this demand, YepAI engineered a multi-agent collaboration system designed for speed, accuracy, and reliability.
Instead of relying on one monolithic model, our architecture runs multiple specialised agents in parallel—sales, support, analytics, and more. These agents exchange information asynchronously, using early-exit logic and fast-path routing to produce the quickest possible answer with the highest confidence.
This system delivers:
42% faster response generation
24% higher intent-recognition accuracy
More coherent, safer, and context-aware replies
For e-commerce merchants, this means customers spend less time waiting and more time buying. Whether it’s abandoned-cart recovery, order modification, product recommendations, or pre-purchase Q&A, the YepAI multi-agent system ensures that every shopper interaction is swift and on-brand.
This architecture is also future-proof, enabling the rapid creation of new agents for specialised retail workflows — such as upsell automation, returns triage, or campaign analytics.
This successful R&D initiative was guided by the expert mentorship of Associate Professor Andy Song of RMIT University. A leading authority in algorithm optimization, robotic path-finding, and AI model efficiency, Dr. Song served as both an academic adviser to the student team and a valued partner to YepAI. His guidance was instrumental in shaping our research roadmap and ensuring our experiments were grounded in scientific rigor while remaining focused on high-impact commercial outcomes.
This partnership demonstrates the strength of combining academic innovation with industry execution — and YepAI’s commitment to bringing research directly into the hands of e-commerce operators.
The integration of these research-driven innovations into YepAI’s AI agent has delivered transformative results across the board. Our platform now operates with a level of performance that sets a new industry standard. Key metrics from our integrated system include:
Response generation speed increased by 42%
User satisfaction scores improved by 33%
Recommendation click-through rate (CTR) rose by 27%
Overall system resource costs reduced by 30%
Thanks to this RMIT partnership, YepAI’s AI agent provides near real-time product discovery with unmatched accuracy, helping online merchants boost customer engagement and drive conversions. This is a clear demonstration of successful AI speed improvement and efficiency gains.
“Our collaboration with RMIT demonstrates how research and commercialization can work hand-in-hand to redefine the future of conversational AI,” says the CEO of YepAI.
“This partnership lets our PhD students see their algorithms come to life in real-world business applications,” adds Associate Professor Andy Song of RMIT.
Looking ahead, YepAI remains dedicated to fostering deep ties with the academic community. We believe that continuous collaboration is the primary driver of meaningful innovation. By continuing our work at the intersection of theoretical discovery and practical application, YepAI will stay at the forefront of developing scalable, responsible, and high-performance AI systems that create lasting value for our clients worldwide.
