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case-study-spoonos

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daniel-azoulai
2025-07-30 15:28:15 -07:00
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qdrant-landing/content/blog/case-study-portfolio-mind.md
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title: "How PortfolioMind Delivered Real-Time Crypto Intelligence with Qdrant" title: "How PortfolioMind Delivered Real-Time Crypto Intelligence with Qdrant"
short_description: "PortfolioMind leverages Qdrant to transform noisy crypto research into personalized real-time intelligence." short_description: "PortfolioMind leverages Qdrant to transform noisy crypto research into personalized real-time intelligence."
description: "Discover how PortfolioMind achieved significant reductions in latency and boosts in engagement by modeling real-time user intent with Qdrant." description: "Discover how PortfolioMind achieved significant reductions in latency and boosts in engagement by modeling real-time user intent with Qdrant."
preview_image: /blog/case-study-portfoliomind/social_preview_partnership-portfoliomind.jpg preview_image: /blog/case-study-portfoliomind/case-study-spoonos-preview.jpg
social_preview_image: /blog/case-study-portfoliomind/social_preview_partnership-portfoliomind.jpg social_preview_image: /blog/case-study-portfoliomind/case-study-spoonos-preview.jpg
date: 2025-07-29 date: 2025-07-29
author: "Daniel Azoulai" author: "Daniel Azoulai"
featured: false featured: false
@@ -34,6 +34,9 @@ PortfolioMind adopted Qdrant to translate intricate user interactions into actio
The system ingests diverse data including news, tokenomics, whale behaviors, portfolio histories, and interactions with DeFi/NFT dashboards, embedding each data type with rich metadata (chain, token symbol, timestamps). Using HDBSCAN clustering, PortfolioMind identifies user-specific micro-interests, creating a dynamic, multivector representation of each user's intent. The system ingests diverse data including news, tokenomics, whale behaviors, portfolio histories, and interactions with DeFi/NFT dashboards, embedding each data type with rich metadata (chain, token symbol, timestamps). Using HDBSCAN clustering, PortfolioMind identifies user-specific micro-interests, creating a dynamic, multivector representation of each user's intent.
![architecture](/blog/case-study-portfoliomind/spoonos-architecture.png)
### Why PortfolioMind chose Qdrant ### Why PortfolioMind chose Qdrant
PortfolioMind previously experimented with other vector databases but selected Qdrant for several critical capabilities: PortfolioMind previously experimented with other vector databases but selected Qdrant for several critical capabilities:
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