HubSpot & Qdrant: Scaling an Intelligent AI Assistant

HubSpot, a global leader in CRM solutions, continuously enhances its product suite with powerful AI-driven features. To optimize Breeze AI, its flagship intelligent assistant, HubSpot chose Qdrant as its vector database.

Challenges Scaling an Intelligent AI

As HubSpot expanded its AI capabilities, it faced several critical challenges in scaling Breeze AI to meet growing user demands:

• Delivering highly personalized, context-aware responses required a robust vector search solution that could retrieve data quickly while maintaining accuracy.
• With increasing user interactions, HubSpot needed a scalable system capable of handling rapid data growth without performance degradation.
• Integration with HubSpot’s existing AI infrastructure had to be swift and easy to support fast-paced development cycles.
• HubSpot sought a future-proof vector search solution that could adapt to emerging AI advancements while maintaining high availability.

These challenges made it essential to find a high-performance, developer-friendly vector database that could power Breeze AI efficiently.

Why HubSpot Chose Qdrant

After evaluating multiple vector databases, HubSpot selected Qdrant because it significantly outperformed alternatives, ensuring that Breeze AI could quickly retrieve and rank relevant data. This was crucial for recommendation systems and contextual content retrieval, where speed and accuracy directly impact user engagement and satisfaction.

Additionally, Hubspot was able to accelerate its development timelines due to Qdrant’s developer-friendly integration process.

Beyond immediate performance gains, HubSpot’s AI infrastructure prepared itself for scale, ensuring that Breeze AI would continue to deliver real-time, relevant responses without compromising speed.

HubSpot also wanted to implement capabilities such as multi-vector search and sparse vectors, which allow for even more precise and contextually aware AI-driven interactions.

Using Qdrant, HubSpot not only solved immediate scalability challenges but also secured a long-term AI search solution capable of evolving alongside its AI roadmap.

Faster, More Accurate Search Improves Customer Satisfaction and Engagement

Since integrating Qdrant, HubSpot has significantly enhanced the performance and intelligence of Breeze AI.

Breeze AI now delivers highly personalized, real-time responses with exceptional contextual awareness, leading to improved customer engagement and satisfaction. With an efficient, accurate search engine, they have reduced retrieval times, ensuring that users receive relevant, timely recommendations without lag.

Moreover, HubSpot can support an increasing volume of AI-powered interactions without worrying about infrastructure bottlenecks. The system adapts to growing datasets, maintaining speed and accuracy even as HubSpot’s customer base and AI use cases expand.

From an engineering perspective, HubSpot has accelerated development cycles, bringing new AI-driven features to market faster. The reduced complexity of vector search integration has freed up engineering resources, allowing the team to focus on enhancing AI models and improving user experiences.

Looking ahead, HubSpot is actively evaluating other features, such as sparse vectors and multi-vector search, to further enhance Breeze AI’s recommendation and retrieval capabilities. These innovations will enable even deeper personalization, reinforcing HubSpot’s leadership in AI-driven customer engagement.

“Qdrant powers our demanding recommendation and RAG applications. We chose it for its ease of deployment and high performance at scale, and we have been consistently impressed with its results. The platform’s continuous feature enhancements and overall performance gains, coupled with their responsiveness, make Qdrant a reliable solution for our AI infrastructure.”

– Srubin Sethu Madhavan, Technical Lead, HubSpot