Case study · From the Pluris libraryReceipt no. 9784
What sucked
Superintelligent's platform offers hundreds of tutorials updated daily, but learners struggled with discovery.
Users needed help finding relevant AI tools for specific use cases without knowing the tool names or whether they existed, and the platform lacked a personalized navigation mechanism.
What they built
Fractional AI built a retrieval-augmented chatbot for Superintelligent's learning platform. It embeds each learner's query, retrieves the most relevant tools from a Pinecone vector database built on the company's proprietary tool catalog, and generates specific, personalized recommendations - with custom scripts keeping the tool database in sync as the daily-updated catalog changes.
What changed
Hundreds of recommendations
Hundreds of personalized tool recommendations have been provided by the chatbot.
Faster learner discovery
Learners spend less time searching and more time learning.
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