Case Study: My AskAI achieves self-improving customer support with Qdrant Cloud

My AskAI deflects 75% of support requests with Qdrant

My AskAI, a managed platform for AI customer support agents, needed a vector search backbone that could handle messy, unstructured support data with strong retrieval and predictable latency as they scaled. Their challenge was to build an infrastructure layer that could support semantic and hybrid search without requiring the team to become full-time database operators, leading them to standardize on Qdrant Cloud.

By implementing Qdrant Cloud as their vector database, My AskAI gained a scalable solution with smooth integrations and an excellent developer experience. The migration resulted in the ability to easily scale infrastructure and iterate on hybrid search, which helped their AI agents deflect around 75 percent of support requests and sustain a resolution rate in the low to mid 70s. Qdrant's platform enabled the next phase of their product: self-learning agents that improve from human interactions.

My AskAI