How to use AI agents to fix broken search in learning platforms

Many learning platforms struggle with the same problem: broken search. Learners can’t find the courses or content they need. It’s a common complaint: “I can’t find that course.” “I can’t find that piece of content.” And it’s frustrating for everyone involved.

‍

In this video Niamh Mulhall, VP of Operation at Mindset AI explains the common challenges learners and businesses face with broken search and how Mindset AI solves them.

The problem learners face

Learners can’t find what they need when they need it, leaving them frustrated. As a result, they give up using the learning platform, turning to Google or tools like ChatGPT and Perplexity for quick answers. 

These tools are fast and intuitive, and learners have grown to expect that level of simplicity and speed from all platforms. When learning platforms fail to deliver, users disengage entirely.

The problem for businesses

Broken search doesn’t just frustrate users. It causes serious issues for businesses too. Low engagement, poor course completion rates, low retention, and even reduced revenue often trace back to one issue: users can’t find what they need. 

When users turn to external tools, businesses lose the opportunity to keep learners engaged within their own ecosystem.

The old way of solving broken search

Traditionally, fixing search problems has been a slow and manual process. Admins spend hours tagging content or sending links directly to learners.

Sending links relies on admins having a mental rolodex of where all the content lives, which is both inefficient and prone to error. 

Tagging, on the other hand, is hard to get right. Too few tags and users can’t narrow down their search; too many tags and it overwhelms the system, often returning irrelevant results. 

Even with these efforts, learners still struggle to find what they need, leading to a poor user experience.

AI agents for better search

With Mindset AI’s agents, broken search becomes a thing of the past. 

These agents help learners find the right courses or resources quickly and easily. By understanding context and intent, they provide accurate and relevant results that meet user expectations.

Agents leverage large language models (LLMs) grounded in your specific content and data. They use Retrieval-Augmented Generation (RAG) techniques to ensure responses are accurate and directly linked to your knowledge base. This means the agents aren’t relying on general information but instead deliver answers tailored to your learners’ needs.

What implementation looks like

At Mindset AI, we follow a four-step approach to implementation:

1. Content understanding: We start by understanding your content—what format it’s in, where it lives, and how often it changes. This ensures the AI has the right foundation to work with.
2. Persona development: Next, we focus on your learners. Who are they? What are their expectations? This step helps us design an agent that aligns with their specific needs.
3. Agent setup: Using the insights from the first two steps, we configure the agent and establish its guardrails. For example, a compliance agent might have strict guardrails and additional accuracy checks, while a coaching agent may have a looser configuration to support a broader range of queries.
4. Testing and iterating: We work with you to test the agent using our testing framework, refining its responses and configuration based on feedback. Once you’re satisfied with the results, we launch the agent. Even after launch, we continue to analyse user interactions and iteratively improve the agent’s performance.

The outcomes

With AI-powered search, learners can find the content they need, when they need it. This improves engagement, course completion rates, and overall user satisfaction. For businesses, it means better retention, higher revenue, and a learning platform that actually delivers value.

Here are some of our favourite success stories:

• Within three weeks of launching with one client, the use of the agent increased course enrolments by 900%.
• In an A/B test, users who engaged with an agent generated 3.4x more revenue than users who didn’t have access to an agent.
• Another customer utilising an FAQ agent saved 40% of their support team’s time within a month of launching.

If your learners are fed up with broken search, it’s time to try something new. AI agents can make your platform easier to use and help learners get the most out of your content.

‍