Case StudyCaso de EstudioCas d'Estudi

Transforming University Support with Multi-Agent AI

A Growing Challenge in Enterprise Support

A leading online university with 70K+ students enrolled sought to enhance its student support services by automating responses to user inquiries while maintaining accuracy and reliability. The existing manual processes were resource-intensive and struggled to scale effectively with growing demand. For a C-suite tasked with growth and efficiency, this wasn’t just a problem—it was a threat to the university’s promise and bottom line.

Advanced AI RAG Custom Solution: A Game-Changing Approach

SEIDOR Opentrends deployed a custom multi-agent AI system powered by Retrieval-Augmented Generation (RAG) designed to think, adapt, and deliver like a human team—but at scale. Here’s how we did it:

  • How Advanced RAG Enhances AI Assistants: Using advanced Retrieval-Augmented Generation (RAG), we clustered the university’s knowledge base into a precision tool, feeding AI (Claude) to craft responses that sounded human, not robotic.
     
  • Developing Intelligent AI Assistant: An AI-driven auditing layer (DeepEval) ensured every answer met strict accuracy standards, flagging edge cases for human review.
     
  • Scaling AI Adoption with Continuous Learning: Every “Not OK” response became a lesson. With continuous retraining and MLOPS, the system got sharper, handling more inquiries with each cycle.

This wasn’t a one-off fix—it built on a Data Office foundation we’d already laid for the online university, a multidisciplinary backbone that gave us the data muscle to pull this Generative AI project off.

multi-agent AI architecture for students support by SEIDOR Opentrends.us

 

The Impact: Transforming Business Processes with Advanced RAG Custom Solutions

By leveraging a multi-agent AI framework, we delivered:

  • 15-20% higher accuracy in automated responses, ensuring reliable support for students
  • Scalable automation: progressively increasing AI-handled inquiries based on performance thresholds.
  • Cost Down, Experience Up: Data-driven improvement through MLOPS and continuous feedback loops

The university didn’t just solve a problem—it transformed its digital support into a competitive edge. What started as a bottleneck became a showcase of innovation, all while keeping quality locked above strict thresholds.

 

The Takeaway for You

For the university’s leadership, this was about more than tech—delivering on their mission without compromise. For you, it’s proof: the right AI, paired with the right strategy, doesn’t just keep the lights on—it lights the way forward. As one university exec put it:

“The Data Office gave us the foundation; this AI system built the future.”