List of Qdrant Customers
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Germany
Since 2010, our global team of researchers has been studying Qdrant customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Qdrant for AI Database from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Qdrant for AI Database include: Deutsche Telekom Germany, a Germany based Communications organisation with 74550 employees and revenues of $27.75 billion, HubSpot, a United States based Professional Services organisation with 8246 employees and revenues of $2.63 billion, Sprinklr, a United States based Professional Services organisation with 3589 employees and revenues of $796.0 million and many others.
Contact us if you need a completed and verified list of companies using Qdrant, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Qdrant customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Deutsche Telekom Germany | Communications | 74550 | $27.7B | Germany | Qdrant | Qdrant | AI Database | 2024 | n/a |
In 2024 Deutsche Telekom integrated Qdrant, an AI Database, into LMOS to scale customer service AI agents across multiple European subsidiaries. The deployment positioned Qdrant as the vector store and similarity search layer supporting conversational agent retrieval and runtime data access for the multi-agent PaaS.
Qdrant was configured to serve high-throughput vector queries and persistent embedding storage, enabling rapid iteration of agent knowledge packs and content indexing. The implementation emphasized scalable vector indexing, similarity search, and low-latency retrieval to support concurrent agents and large conversation volumes.
Integration points centered on embedding Qdrant within LMOS multi-agent runtime workflows, routing retrieval requests from agent orchestration modules to the Qdrant cluster. Operational coverage spans Deutsche Telekom customer service use cases across multiple European subsidiaries, with Qdrant processing millions of conversations according to the case study.
The case study reports that Qdrant reduced agent development time from approximately 15 days to about 2 days, and that the platform was able to handle millions of conversations. Governance and rollout details were executed at the LMOS platform level to enable centralized access for agent teams and to standardize retrieval workflows for customer service AI agents.
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HubSpot | Professional Services | 8246 | $2.6B | United States | Qdrant | Qdrant | AI Database | 2025 | n/a |
In 2025 HubSpot implemented Qdrant to power Breeze AI, its intelligent assistant within HubSpot CRM in the United States. Qdrant is an AI Database that HubSpot integrated into its AI stack to enable personalized, context aware retrieval and recommendations for CRM workflows.
The implementation concentrated on high throughput vector retrieval and semantic search capabilities native to an AI Database, configured to serve Breeze AI query workloads and to support embedding based nearest neighbor lookups. HubSpot configured Qdrant to index contextual signals from CRM records and knowledge assets, aligning similarity search and recommendation pipelines with product team requirements for low latency and relevance.
Integration work focused on embedding pipelines and the existing AI serving layer, bringing Qdrant into HubSpot's model inference and retrieval orchestration. Operational responsibility rested with AI engineering and product teams who coordinated rollout of Breeze AI features across the CRM product. The case study reports faster, more accurate retrieval and accelerated feature delivery after integrating Qdrant into HubSpot's AI stack.
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Sprinklr | Professional Services | 3589 | $796M | United States | Qdrant | Qdrant | AI Database | 2024 | n/a |
In 2024, Sprinklr adopted Qdrant, an AI Database, to power retrieval for RAG, live chat, and other AI-driven features across its Unified-CXM platform in the United States. The deployment used a managed Qdrant service on AWS to support production vector search workloads tied to customer experience workflows.
Implementation centered on vector similarity search and persistent vector stores to enable retrieval augmented generation and real time chat retrieval. Configuration work included index tuning and performance optimization for large vector sets, aligned to P99 latency targets and embedding-driven retrieval patterns common to AI Database architectures.
Qdrant retrieval endpoints were integrated into Sprinklr's Unified-CXM orchestration and AI feature pipelines to serve RAG workflows, live chat, and broader AI-driven capabilities across CX functions. Sprinklr's internal benchmarks reported approximately 30% infrastructure cost reduction and low P99 latencies of about 20 milliseconds on 1 million vectors after adopting Qdrant, reflecting the implementation's performance and cost outcomes.
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Buyer Intent: Companies Evaluating Qdrant
- Michael Cizmar + Associates., a United States based Professional Services organization with 10 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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