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 draft: false
 title: "Airbyte and Qdrant Hybrid Cloud"
 short_description: "Elevate Your Data Performance With Airbyte and Qdrant Hybrid Cloud." 
 description: "Elevate Your Data Performance With Airbyte and Qdrant Hybrid Cloud."
 preview_image: /blog/hybrid-cloud-airbyte/hybrid-cloud-airbyte.png
 date: 2024-04-10T00:00:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Elevate Your Data Performance With Airbyte and Qdrant Hybrid Cloud
 In their mission to support large-scale AI innovation, Airbyte and Qdrant are collaborating on the launch of Qdrant’s new offering - Qdrant Hybrid Cloud. This collaboration allows users to leverage the synergistic capabilities of both Airbyte and Qdrant within a private infrastructure. Qdrant’s new offering represents the first managed vector database that can be deployed in any environment. Businesses optimizing their data infrastructure with Airbyte are now able to host a vector database either on premise, or on a public cloud of their choice - while still reaping the benefits of a managed database product.
 This is a major step forward in offering enterprise customers incredible synergy for maximizing the potential of their AI data. Qdrant's new Kubernetes-native design, coupled with Airbyte’s powerful data ingestion pipelines meet the needs of developers who are both prototyping and building production-level apps. Airbyte simplifies the process of data integration by providing a platform that connects to various sources and destinations effortlessly. Moreover, Qdrant Hybrid Cloud leverages advanced indexing and search capabilities to empower users to explore and analyze their data efficiently.
 In a major benefit to Generative AI, businesses can leverage Airbyte's data replication capabilities to ensure that their data in Qdrant Hybrid Cloud is always up to date. This empowers all users of Retrieval Augmented Generation (RAG) applications with effective analysis and decision-making potential, all based on the latest information. Furthermore, by combining Airbyte's platform and Qdrant's hybrid cloud infrastructure, users can optimize their data operations while keeping costs under control via flexible pricing models tailored to individual usage requirements.
 // Insert quote from Airbyte
 ## Optimizing Your GenAI Data Stack With Airbyte and Qdrant Hybrid Cloud
 By integrating Airbyte with Qdrant Hybrid Cloud, you can achieve seamless data ingestion from diverse sources into Qdrant's powerful indexing system. This integration enables you to derive valuable insights from your data. Here are some key advantages:
 **Effortless Data Integration:** Airbyte's intuitive interface lets you set up data pipelines that extract, transform, and load (ETL) data from various sources into Qdrant. Additionally, Qdrant Hybrid Cloud’s Kubernetes-native architecture means that the destination vector database can now be deployed in a few clicks to any environment. With such flexibility, you can supply even the most advanced RAG applications with optimal data pipelines.
 **Scalability and Performance:** With Airbyte and Qdrant Hybrid Cloud, you can scale your data infrastructure according to your needs. Whether you're dealing with terabytes or petabytes of data, this combination ensures optimal performance and scalability. This is a robust setup that is designed to meet the needs of large enterprises, ensuring a full spectrum of solutions for various projects and workloads.
 **Powerful Indexing and Search:** Qdrant Hybrid Cloud’s architecture combines the scalability of cloud infrastructure with the performance of on-premises indexing. Qdrant's advanced algorithms enable lightning-fast search and retrieval of data, even across large datasets.
 **Open-Source Compatibility:** Airbyte and Qdrant pride themselves on maintaining a reliable and mature integration that brings peace of mind to those prototyping and deploying large-scale AI solutions. Extensive open-source documentation and code samples help users of all skill levels in leveraging highly advanced features of data ingestion and vector search.
 ## Build a Modern GenAI Application With Qdrant Hybrid Cloud and Airbyte
 ![hybrid-cloud-airbyte-tutorial](/blog/hybrid-cloud-airbyte/hybrid-cloud-airbyte-tutorial.png)
 We put together an end-to-end tutorial to show you how to build a GenAI application with Qdrant Hybrid Cloud and Airbyte’s advanced data pipelines.
 **Tutorial: Build a RAG System to Answer Customer Support Queries**
 Learn how to set up a private AI service that addresses customer support issues with high accuracy and effectiveness. By leveraging Airbyte’s data pipelines with Qdrant Hybrid Cloud, you will create a customer support system that is always synchronized with up-to-date knowledge.
 **> Try the Tutorial**
 **Documentation: Deploy Qdrant in a few clicks**
 Our simple Kubernetes-native design lets you deploy Qdrant Hybrid Cloud on your hosting platform of choice in just a few steps. Learn how in our documentation.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
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 title: "Cohere and Qdrant Hybrid Cloud"
 short_description: "Qdrant Hybrid Cloud and Cohere Collaborate to Support Enterprise GenAI Solutions." 
 description: "Qdrant Hybrid Cloud and Cohere Collaborate to Support Enterprise GenAI Solutions."
 preview_image: /blog/hybrid-cloud-cohere/hybrid-cloud-cohere.png
 date: 2024-04-10T00:01:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Qdrant Hybrid Cloud and Cohere Collaborate to Support Enterprise GenAI Solutions
 We’re excited to share that Qdrant and Cohere are partnering on the launch of Qdrant Hybrid Cloud to enable global audiences to build and scale their AI applications quickly and securely. With Cohere's world-class large language models (LLMs), getting the most out of vector search becomes incredibly easy. Qdrant's new Hybrid Cloud offering and its Kubernetes-native design can be coupled with Cohere's powerful models and APIs. This combination allows for simple setup when prototyping and deploying AI solutions.
 It’s no secret that Retrieval Augmented Generation (RAG) has shown to be a powerful method of building conversational AI products, such as chatbots or customer support systems. With Cohere's managed LLM service, scientists and developers can tap into state-of-the-art text generation and understanding capabilities, all accessible via API. Qdrant Hybrid Cloud seamlessly integrates with Cohere’s foundation models, enabling convenient data vectorization and highly accurate semantic search.
 With Qdrant Hybrid Cloud, users have the flexibility to deploy their vector database in an environment of their choice. By using container-based scalable deployments, global businesses can keep both products deployed in the same hosting architecture. By combining Cohere’s foundation models with Qdrant’s vector search capabilities, developers can create robust and scalable GenAI applications tailored to meet the demands of modern enterprises. This powerful combination empowers organizations to build strong and secure applications that search, understand meaning and converse in text.
 // Insert quote from Cohere
 ---
 ## Take Full Control of Your GenAI Application with Qdrant Hybrid Cloud and Cohere
 Building apps with Qdrant Hybrid Cloud and Cohere’s models comes with several key advantages:
 **Data Sovereignty:** Should you wish to keep both deployment together, this integration guarantees that your vector database is hosted in proximity to the foundation models and proprietary data, thereby reducing latency, supporting data locality, and safeguarding sensitive information to comply with regulatory requirements, such as GDPR.
 **Massive Scale Support:** Users can achieve remarkable efficiency and scalability in running complex queries across vast datasets containing billions of text objects and millions of users. This integration enables lightning-fast retrieval of relevant information, making it ideal for enterprise-scale applications where speed and accuracy are paramount.
 **Cost Efficiency:** By leveraging Qdrant's quantization for efficient data handling and pairing it with Cohere's scalable and affordable pricing structure, the price/performance ratio of this integration is next to none. Companies who are just getting started with both will have a minimal upfront investment and optimal cost management going forward.
 ## Start Building Your New App With Cohere and Qdrant Hybrid Cloud
 ![hybrid-cloud-cohere-tutorial](/blog/hybrid-cloud-cohere/hybrid-cloud-cohere-tutorial.png)
 We put together an end-to-end tutorial to show you how to build a GenAI application with Qdrant Hybrid Cloud and Cohere’s embeddings.
 **Tutorial: Build a RAG System to Answer Customer Support Queries**
 Learn how to set up a private AI service that addresses customer support issues with high accuracy and effectiveness. By leveraging Cohere’s models with Qdrant Hybrid Cloud, you will create a fully private customer support system.
 **> Try the Tutorial**
 **Documentation: Deploy Qdrant in a few clicks**
 Our simple Kubernetes-native design lets you deploy Qdrant Hybrid Cloud on your hosting platform of choice in just a few steps. Learn how in our documentation.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
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 draft: false
 title: "deepset and Qdrant Hybrid Cloud"
 short_description: "Qdrant Hybrid Cloud and Haystack by deepset: A Winning Combination for Enterprise-Scale RAG." 
 description: "Qdrant Hybrid Cloud and Haystack by deepset: A Winning Combination for Enterprise-Scale RAG."
 preview_image: /blog/hybrid-cloud-haystack/hybrid-cloud-haystack.png
 date: 2024-04-10T00:02:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Qdrant Hybrid Cloud and Haystack by deepset: A Winning Combination for Enterprise-Scale RAG
 We’re excited to share that Qdrant and Haystack are continuing to expand their seamless integration to the new Qdrant Hybrid Cloud offering, allowing developers to deploy a managed vector database in their own environment of choice. Earlier this year, both Qdrant and Haystack, started to address their user’s growing need for production-ready retrieval-augmented-generation (RAG) deployments. The ability to build and deploy AI apps anywhere now allows for complete data sovereignty and control. This gives large enterprise customers the peace of mind they need before they expand AI functionalities throughout their operations.
 With a highly customizable framework like Haystack, implementing vector search becomes incredibly simple. Qdrant's new Qdrant Hybrid Cloud offering and its Kubernetes-native design supports customers all the way from a simple prototype setup to a production scenario on any hosting platform. Users can attach AI functionalities to their existing in-house software by creating custom integration components. Don’t forget, both products are open-source and highly modular!
 With Haystack and Qdrant Hybrid Cloud, the path to production has never been clearer. The elaborate integration of Qdrant as a Document Store simplifies the deployment of Haystack-based AI applications in any production-grade environment. Coupled with Qdrant’s Hybrid Cloud offering, your application can be deployed anyplace, on your own terms.
 “We hope that with Haystack 2.0 and our growing partnerships such as what we have here with Qdrant Hybrid Cloud, engineers are able to build AI systems with full autonomy. Both in how their pipelines are designed, and how their data are managed.” Tuana Çelik, Developer Relations Lead, deepset.
 ## Simplifying RAG Deployment: Qdrant Hybrid Cloud and Haystack 2.0 Integration
 Building apps with Qdrant Hybrid Cloud and deepset’s framework has become even simpler with Haystack 2.0. Both products are completely optimized for RAG in production scenarios. Here are some key advantages:
 **Mature Integration:** You can connect your Haystack pipelines to Qdrant in a few lines of code. Qdrant Hybrid Cloud leverages the existing “Document Store” integration for data sources.This common interface makes it easy to access Qdrant as a data source from within your existing setup.
 **Production Readiness:** With deepset’s new product [Hayhooks](https://docs.haystack.deepset.ai/docs/hayhooks), you can generate RESTful APIs from Haystack pipelines. This simplifies the deployment process and makes the service easily accessible by developers using Qdrant Hybrid Cloud to prepare RAG systems for production.
 **Flexible & Customizable:** The open-source nature of Qdrant and Haystack’s 2.0 makes it easy to extend the capabilities of both products through customization. When tailoring vector RAG systems to their own needs, users can develop custom components and plug them into both Qdrant Hybrid Cloud and Haystack for maximum modularity. [Creating custom components](https://docs.haystack.deepset.ai/docs/custom-components) is a core functionality.
 ## Learn How to Build a Production-Level RAG Service With Qdrant and deepset
 ![hybrid-cloud-haystack-tutorial](/blog/hybrid-cloud-haystack/hybrid-cloud-haystack-tutorial.png)
 To get you started, we created a comprehensive tutorial that shows how to build next-gen AI applications with Qdrant Hybrid Cloud using deepset’s Haystack framework.
 **Tutorial: Private Chatbot for Interactive Learning**
 Learn how to develop a tutor chatbot from online course materials. You will create a Retrieval Augmented Generation (RAG) pipeline with Haystack for enhanced generative AI capabilities and Qdrant Hybrid Cloud for vector search. By deploying every tool on RedHat OpenShift, you will ensure complete privacy and data sovereignty, whereby no course content leaves your cloud.
 **> Try the Tutorial**
 **Documentation: Deploy Qdrant in a few clicks**
 Our simple Kubernetes-native design lets you deploy Qdrant Hybrid Cloud on your hosting platform of choice in just a few steps. Learn how in our documentation.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
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 ---
 draft: false
 title: "Jina AI and Qdrant Hybrid Cloud"
 short_description: "Develop Cutting-Edge GenAI Apps with Jina AI and Qdrant Hybrid Cloud." 
 description: "Develop Cutting-Edge GenAI Apps with Jina AI and Qdrant Hybrid Cloud."
 preview_image: /blog/hybrid-cloud-jinaai/hybrid-cloud-jinaai.png
 date: 2024-04-10T00:03:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Develop Cutting-Edge GenAI Apps with Jina AI and Qdrant Hybrid Cloud
 We're thrilled to announce the collaboration between Qdrant and Jina AI for the launch of Qdrant Hybrid Cloud, empowering users worldwide to rapidly and securely develop and scale their AI applications. By leveraging Jina AI's top-tier large language models (LLMs), engineers and scientists can optimize their vector search efforts. Qdrant's latest Hybrid Cloud solution, designed natively with Kubernetes, seamlessly integrates with Jina AI's robust embedding models and APIs. This synergy streamlines both prototyping and deployment processes for AI solutions.
 Retrieval Augmented Generation (RAG) is broadly adopted as the go-to Generative AI solution, as it enables powerful and cost-effective chatbots, customer support agents and other forms of semantic search applications. Through Jina AI's managed service, users gain access to cutting-edge text generation and comprehension capabilities, conveniently accessible through an API. Qdrant Hybrid Cloud effortlessly incorporates Jina AI's embedding models, facilitating smooth data vectorization and delivering exceptionally precise semantic search functionality.
 With Qdrant Hybrid Cloud, users have the flexibility to deploy their vector database in an environment of their choice. By using container-based scalable deployments, global businesses can keep both products deployed in the same hosting architecture. By combining Jina AI’s models with Qdrant’s vector search capabilities, developers can create robust and scalable applications tailored to meet the demands of modern enterprises. This combination allows organizations to build strong and secure Generative AI solutions.
 // Insert quote from JinaAI
 ## Benefits of Qdrant’s Vector Search With Jina AI Embeddings in Enterprise RAG Scenarios
 Building apps with Qdrant Hybrid Cloud and Jina AI’s embeddings comes with several key advantages:
 **Seamless Deployment:** Jina AI’s best-in-class embedding APIs can be combined with Qdrant Hybrid Cloud’s Kubernetes-native architecture to deploy flexible and platform-agnostic AI solutions in a few minutes to any environment. This combination is purpose built for both prototyping and scalability, so that users can put together advanced RAG solutions anyplace with minimal effort.
 **Scalable Vector Search:** Once deployed to a customer’s host of choice, Qdrant Hybrid Cloud provides a fully managed vector database that lets users effortlessly scale the setup through vertical or horizontal scaling. Deployed in highly secure environments, this is a robust setup that is designed to meet the needs of large enterprises, ensuring a full spectrum of solutions for various projects and workloads.
 **Cost Efficiency:** By leveraging Jina AI's scalable and affordable pricing structure and pairing it with Qdrant's quantization for efficient data handling, this integration offers great value for its cost. Companies who are just getting started with both will have a minimal upfront investment and optimal cost management going forward.
 ## Start Building Gen AI Apps With Jina AI and Qdrant Hybrid Cloud
 ![hybrid-cloud-jinaai-tutorial](/blog/hybrid-cloud-jinaai/hybrid-cloud-jinaai-tutorial.png)
 To get you started, we created a comprehensive tutorial that shows how to build a modern GenAI application with Qdrant Hybrid Cloud and Jina AI embeddings.
 **Tutorial: Hybrid Search for Household Appliance Manuals**
 Learn how to build an app that retrieves information from PDF user manuals to enhance user experience for companies that sell household appliances. The system will leverage Jina AI embeddings and Qdrant Hybrid Cloud for enhanced generative AI capabilities, while the RAG pipeline will be tied together using the LlamaIndex framework. This example demonstrates how complex tables in PDF documentation can be processed as high quality embeddings with no extra configuration. By introducing Hybrid Search from Qdrant, the RAG functionality is highly accurate.
 **> Try the Tutorial**
 **Documentation: Deploy Qdrant in a few clicks**
 Our simple Kubernetes-native design lets you deploy Qdrant Hybrid Cloud on your hosting platform of choice in just a few steps. Learn how in our documentation.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
@@ -0,0 +1,53 @@
 ---
 draft: false
 title: "LlamaIndex and Qdrant Hybrid Cloud"
 short_description: "Unlock New RAG Opportunities with Qdrant Hybrid Cloud and LlamaIndex." 
 description: "Unlock New RAG Opportunities with Qdrant Hybrid Cloud and LlamaIndex."
 preview_image: /blog/hybrid-cloud-llamaindex/hybrid-cloud-llamaindex.png
 date: 2024-04-10T00:04:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Unlock New RAG Opportunities with Qdrant Hybrid Cloud and LlamaIndex
 We're happy to announce the collaboration between LlamaIndex and Qdrant’s new Hybrid Cloud launch, aimed at empowering engineers and scientists worldwide to swiftly and securely develop and scale their GenAI applications. By leveraging LlamaIndex's robust framework, users can maximize the potential of vector search and create stable and effective AI products. Qdrant Hybrid Cloud offers the same Qdrant functionality on a Kubernetes-based architecture, which further expands the ability of LlamaIndex to support any user on any environment.
 With Qdrant Hybrid Cloud, users have the flexibility to deploy their vector database in an environment of their choice. By using container-based scalable deployments, companies can leverage a cutting-edge framework like LlamaIndex, while staying deployed in the same hosting architecture as data sources, embedding models and LLMs. This powerful combination empowers organizations to build strong and secure applications that search, understand meaning and converse in text.
 While LLMs are trained on a great deal of data, they are not trained on user-specific data, which may be private or highly specific. LlamaIndex meets this challenge by adding context to LLM-based generation methods. In turn, Qdrant’s popular vector database sorts through semantically relevant information, which can further enrich the performance gains from LlamaIndex’s data connection features. With LlamaIndex, users can tap into state-of-the-art functions to query, chat, sort or parse data. Through the integration of Qdrant Hybrid Cloud and LlamaIndex developers can conveniently vectorize their data and perform highly accurate semantic search - all within their own environment.
 // Possibility to insert quote from LlamaIndex
 ## Reap the Benefits of Advanced Integration Features With Qdrant and LlamaIndex
 Building apps with Qdrant Hybrid Cloud and LlamaIndex comes with several key advantages:
 **Seamless Deployment:** Qdrant Hybrid Cloud’s Kubernetes-native architecture lets you deploy Qdrant in a few clicks, to an environment of your choice. Combined with the flexibility afforded by LlamaIndex, users can put together advanced RAG solutions anyplace at minimal effort.
 **Open-Source Compatibility:** LlamaIndex and Qdrant pride themselves on maintaining a reliable and mature integration that brings peace of mind to those prototyping and deploying large-scale AI solutions. Extensive documentation, code samples and tutorials support users of all skill levels in leveraging highly advanced features of data ingestion and vector search.
 **Advanced Search Features:** LlamaIndex comes with built-in Qdrant Hybrid Search functionality, which combines search results from sparse and dense vectors. As a highly sought-after use case, hybrid search is easily accessible from within the LlamaIndex ecosystem. Deploying this particular type vector search on Hybrid Cloud is a matter of a few lines of code.
 ## Start Building With LlamaIndex and Qdrant Hybrid Cloud: Hybrid Search in Complex PDF Documentation Use Cases
 ![hybrid-cloud-llamaindex-tutorial](/blog/hybrid-cloud-llamaindex/hybrid-cloud-llamaindex-tutorial.png)
 To get you started, we created a comprehensive tutorial that shows how to build next-gen AI applications with Qdrant Hybrid Cloud using the LlamaIndex framework and the LlamaParse API.
 **Tutorial: Hybrid Search for Household Appliance Manuals**
 Use this end-to-end tutorial to create a system that retrieves information from complex user manuals in PDF format to enhance user experience for companies that sell household appliances. You will build a RAG pipeline with LlamaIndex leveraging Qdrant Hybrid Cloud for enhanced generative AI capabilities. The LlamaIndex integration shows how complex tables inside of items’ PDF documents can be processed via hybrid vector search with no additional configuration.
 **> Try the Tutorial**
 **Documentation: Deploy Qdrant in a few clicks**
 Our simple Kubernetes-native design lets you deploy Qdrant Hybrid Cloud on your hosting platform of choice in just a few steps. Learn how in our documentation.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
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 ---
 draft: false
 title: "OVHcloud and Qdrant Hybrid Cloud"
 short_description: "Qdrant and OVHcloud Collaborate To Bring Vector Search to Startups and Enterprises in Europe With A Strong Focus on Data Control and Privacy." 
 description: "Qdrant and OVHcloud Collaborate To Bring Vector Search to Startups and Enterprises in Europe With A Strong Focus on Data Control and Privacy."
 preview_image: /blog/hybrid-cloud-ovhcloud/hybrid-cloud-ovhcloud.png
 date: 2024-04-10T00:05:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Qdrant and OVHcloud Collaborate To Bring Vector Search to Startups and Enterprises in Europe With A Strong Focus on Data Control and Privacy
 With the official release of Qdrant Hybrid Cloud, businesses running their data infrastructure on OVHcloud are now able to deploy a fully managed vector database in their existing OVHcloud environment. We are excited about this partnership, which has been established through the [OVHcloud Open Trusted Cloud](https://opentrustedcloud.ovhcloud.com/en/) program, as it is based on our shared understanding of the importance of trust, control, and data privacy in the context of the emerging landscape of enterprise-grade AI applications. As part of this collaboration, we are also providing a detailed use case tutorial on building a recommendation system with ‘collaborative filtering using sparse vectors’ that demonstrates the benefits of running Qdrant Hybrid Cloud on OVHcloud.
 Deploying Qdrant Hybrid Cloud on OVHcloud's infrastructure represents a significant leap for European businesses invested in AI-driven projects, as this collaboration underscores the commitment to meeting the rigorous requirements for data privacy and control of European startups and enterprises building AI solutions. As businesses are progressing on their AI journey, they require dedicated solutions that allow them to make their data accessible for machine learning and AI projects, without having it leave the company's security perimeter. Prioritizing data sovereignty, a crucial aspect in today's digital landscape, will help startups and enterprises accelerate their AI agenda’s and build even more differentiating AI-enabled applications. The ability of running Qdrant Hybrid Cloud on OVHcloud not only underscores the commitment to innovative, secure AI solutions but also ensures that companies can navigate the complexities of AI and machine learning workloads with the flexibility and security required.
 // Potential quote from OVHcloud
 ## Qdrant & OVHcloud: High Performance Vector Search With Full Data Control
 Through the seamless integration between Qdrant Hybrid Cloud and OVHcloud, developers and businesses are able to deploy the fully managed vector database within their existing OVHcloud setups in minutes, enabling faster, more accurate AI-driven insights.
 - **Simple setup:** With the seamless “one-click” installation, developers are able to deploy Qdrant’s fully managed vector database to their existing OVHcloud environment.
 - **Trust and data sovereignty**: Deploying Qdrant Hybrid Cloud on OVHcloud enables developers with vector search that prioritizes data sovereignty, a crucial aspect in today's AI landscape where data privacy and control are essential. True to its “Sovereign by design” DNA, OVHcloud guarantees that all the data stored are immune to extraterritorial laws and comply with the highest security standards.
 - **Open standards and open ecosystem**: OVHcloud’s commitment to open standards and an open ecosystem not only facilitates the easy integration of Qdrant Hybrid Cloud with OVHcloud’s AI services and GPU-powered instances but also ensures compatibility with a wide range of external services and applications, enabling seamless data workflows across the modern AI stack.
 - **Cost efficient sector search:** By leveraging Qdrant's quantization for efficient data handling and pairing it with OVHcloud's eco-friendly, water-cooled infrastructure, known for its superior price/performance ratio, this collaboration provides a strong foundation for cost efficient vector search.
 ## Build a Recommendation System with Collaborative Filtering Using Sparse Vectors with Qdrant Hybrid Cloud and OVHcloud
 ![hybrid-cloud-ovhcloud-tutorial](/blog/hybrid-cloud-ovhcloud/hybrid-cloud-ovhcloud-tutorial.png)
 To show how Qdrant Hybrid Cloud deployed on OVHcloud allows developers to leverage the benefits of an AI use case that is completely run within the existing infrastructure, we put together a comprehensive use case tutorial. This tutorial guides you through creating a recommendation system using collaborative filtering and sparse vectors with Qdrant Hybrid Cloud on OVHcloud. It employs the Movielens dataset for practical application, providing insights into building efficient, scalable recommendation engines suitable for developers and data scientists looking to leverage advanced vector search technologies within a secure, GDPR-compliant European cloud infrastructure.
 **> Explore Tutorial**
 ## Get started today and leverage the benefits of Qdrant Hybrid Cloud**
 Setting up Qdrant Hybrid Cloud on OVHcloud is straightforward and quick, thanks to the intuitive integration with Kubernetes. Here's how:
 - **Hybrid Cloud Activation**: Log into your Qdrant account and enable 'Hybrid Cloud'.
 - **Cluster Integration**: Add your OVHcloud Kubernetes clusters as a private region in the Hybrid Cloud settings.
 - **Effortless Deployment**: Use the Qdrant Management Console for easy deployment and management of Qdrant clusters on OVHcloud.
 **> View Documentation**
 Learn more about Qdrant Hybrid Cloud in the official release blog. Ready to get started? Create your Qdrant Hybrid Cloud cluster in a few minutes by creating your Qdrant Cloud account.
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 ---
 draft: false
 title: "Scaleway and Qdrant Hybrid Cloud"
 short_description: "Qdrant and Scaleway Empower Innovation in AI with Launch of Hybrid Cloud Vector Search for Startups and Developers." 
 description: "Qdrant and Scaleway Empower Innovation in AI with Launch of Hybrid Cloud Vector Search for Startups and Developers."
 preview_image: /blog/hybrid-cloud-scaleway/hybrid-cloud-scaleway.png
 date: 2024-04-10T00:06:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Qdrant and Scaleway Empower Innovation in AI with Launch of Hybrid Cloud Vector Search for Startups and Developers
 In a move to empower the next wave of AI innovation, Qdrant and Scaleway collaborate to introduce Qdrant Hybrid Cloud, a fully managed vector database that can be deployed on existing Scaleway environments. This collaboration is set to democratize access to advanced AI capabilities, enabling developers to easily deploy and scale vector search technologies within Scaleway's robust and developer-friendly cloud infrastructure. By focusing on the unique needs of startups and the developer community, Qdrant and Scaleway are providing access to intuitive and easy to use tools, making cutting-edge AI more accessible than ever before.
 Building on this vision, the integration between Scaleway and Qdrant Hybrid Cloud leverages the strengths of both Qdrant, with its leading open-source vector database, and Scaleway, known for its innovative and scalable cloud solutions. This integration means startups and developers can now harness the power of vector search - essential for AI applications like recommendation systems, image recognition, and natural language processing - within their existing environment without the complexity of maintaining such advanced setups.
 *"With our partnership with Qdrant, Scaleway reinforces its status as Europe's leading cloud provider for AI innovation. The integration of Qdrant's fast and accurate vector database enriches our expanding suite of AI solutions. This means you can build smarter, faster AI projects with us, worry-free about performance and security." Frédéric BARDOLLE, Lead PM AI @ Scaleway*
 ## Developing a Retrieval Augmented Generation (RAG) Application with Qdrant Hybrid Cloud, Scaleway, and LangChain
 Retrieval Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating vector search to provide precise, context-rich responses. This combination allows LLMs to access and incorporate specific data in real-time, vastly improving the quality of AI-generated content.
 RAG applications often rely on sensitive or proprietary internal data, emphasizing the importance of data sovereignty. Running the entire stack within your own environment becomes crucial for maintaining control over this data. Qdrant Hybrid Cloud deployed on Scaleway addresses this need perfectly, offering a secure, scalable platform that respects data sovereignty requirements while leveraging the full potential of RAG for sophisticated AI solutions.
 ![hybrid-cloud-scaleway-tutorial](/blog/hybrid-cloud-scaleway/hybrid-cloud-scaleway-tutorial.png)
 We created a tutorial that guides you through setting up and leveraging Qdrant Hybrid Cloud on Scaleway for a RAG application, providing insights into efficiently managing data within a secure, sovereign framework. It highlights practical steps to integrate vector search with LLMs, optimizing the generation of high-quality, relevant AI content, while ensuring data sovereignty is maintained throughout.
 **> Explore Tutorial**
 ## The Benefits of Running Qdrant Hybrid Cloud on Scaleway
 Choosing Qdrant Hybrid Cloud and Scaleway for AI applications offers several key advantages:
 - **AI-Focused Resources:** Scaleway aims to be the cloud provider of choice for AI companies, offering the resources and infrastructure to power complex AI and machine learning workloads, helping to advance the development and deployment of AI technologies. This paired with Qdrant Hybrid Cloud provides a strong foundational platform for advanced AI applications.
 - **Scalable Vector Search:** Qdrant Hybrid Cloud provides a fully managed vector database that allows to effortlessly scale the setup through vertical or horizontal scaling. Deployed on Scaleway, this is a robust setup that is designed to meet the needs of businesses at every stage of growth, from startups to large enterprises, ensuring a full spectrum of solutions for various projects and workloads.
 - **European Roots and Focus**: With a strong presence in Europe and a commitment to supporting the European tech ecosystem, Scaleway is ideally positioned to partner with European-based companies like Qdrant, providing local expertise and infrastructure that aligns with European regulatory standards.
 - **Sustainability Commitment**: Scaleway leads with an eco-conscious approach, featuring adiabatic data centers that significantly reduce cooling costs and environmental impact. Scaleway prioritizes extending hardware lifecycle beyond industry norms to lessen our ecological footprint.
 ## Get Started In a Few Seconds
 Setting up Qdrant Hybrid Cloud on Scaleway is streamlined and quick, thanks to its Kubernetes-native architecture. Follow these simple three steps to launch:
 1. **Activate Hybrid Cloud**: First, log into your Qdrant account and select ‘Hybrid Cloud’ to activate.
 2. **Integrate Your Clusters**: Navigate to the Hybrid Cloud settings and add your Scaleway Kubernetes clusters as a private region.
 3. **Simplified Management**: Use the Qdrant Management Console for easy creation and oversight of your Qdrant clusters on Scaleway.
 For more comprehensive guidance, our documentation provides step-by-step instructions for deploying Qdrant on Scaleway.
 **> View Documentation**
 Read more about Qdrant Hybrid Cloud in our official release blog. To deploy your first cluster in a few clicks, begin by creating a Qdrant Cloud account. Our Hybrid Cloud docs will help you with the rest.
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 ---
 draft: false
 title: "STACKIT and Qdrant Hybrid Cloud"
 short_description: "Empowering German AI Development with a Data Privacy-First Platform." 
 description: "Empowering German AI Development with a Data Privacy-First Platform."
 preview_image: /blog/hybrid-cloud-stackit/hybrid-cloud-stackit.png
 date: 2024-04-10T00:07:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ### Qdrant Hybrid Cloud and STACKIT: Empowering German AI Development with a Data Privacy-First Platform
 Qdrant and STACKIT are thrilled to announce that developers are now able to deploy a fully managed vector database to their STACKIT environment with the introduction of Qdrant Hybrid Cloud. This is a great step forward for the German AI ecosystem as it enables developers and businesses to build cutting edge AI applications that run on German data centers with full control over their data.
 Vector databases are an essential component of the modern AI stack. They enable rapid and accurate retrieval of high-dimensional data, crucial for powering search, recommendation systems, and augmenting machine learning models. In the rising field of GenAI, vector databases power retrieval-augmented-generation (RAG) scenarios as they are able to enhance the output of large language models (LLMs) by injecting relevant contextual information. However, this contextual information is often rooted in confidential internal or customer-related information, which is why enterprises are in pursuit of solutions that allow them to make this data available for their AI applications without compromising data privacy, losing data control, or letting data exit the company's secure environment.
 Qdrant Hybrid Cloud is the first managed vector database that can be deployed in an existing STACKIT environment. The Kubernetes-native setup allows businesses to operate a fully managed vector database, while maintaining control over their data through complete data isolation. Qdrant Hybrid Cloud's managed service seamlessly integrates into STACKIT's cloud environment, allowing businesses to deploy fully managed vector search workloads, secure in the knowledge that their operations are backed by the stringent data protection standards of Germany's data centers and in full compliance with GDPR. This setup not only ensures that data remains under the businesses control but also paves the way for secure, AI-driven application development.
 ## Key Features and Benefits of Qdrant on STACKIT:
 - **Seamless Integration and Deployment**: With Qdrant’s Kubernetes-native design, businesses can effortlessly connect their STACKIT cloud as a private region, enabling a one-step, scalable Qdrant deployment.
 - **Enhanced Data Privacy**: Leveraging STACKIT's German data centers ensures that all data processing complies with GDPR and other relevant European data protection standards, providing businesses with unparalleled control over their data.
 - **Scalable and Managed AI Solutions**: Deploying Qdrant on STACKIT provides a fully managed vector search engine with the ability to scale vertically and horizontally, with robust support for zero-downtime upgrades and disaster recovery, all within STACKIT's secure infrastructure.
 ## Use Case: AI-enabled Contract Management built with Qdrant Hybrid Cloud, STACKIT, and Aleph Alpha
 ![hybrid-cloud-stackit-tutorial](/blog/hybrid-cloud-stackit/hybrid-cloud-stackit-tutorial.png)
 To demonstrate the power of Qdrant Hybrid Cloud on STACKIT, we’ve developed a comprehensive tutorial showcasing how to build secure, AI-driven applications focusing on data sovereignty. This tutorial specifically shows how to build a contract management platform that enables users to upload documents (PDF or DOCx), which are then segmented for searchable access. Designed with multitenancy, users can only access their team or organization's documents. It also features custom sharding for location-specific document storage. Beyond search, the application offers rephrasing of document excerpts for clarity to those without context.
 **> Explore Tutorial**
 ## Start Using Qdrant with STACKIT
 Deploying Qdrant Hybrid Cloud on STACKIT is straightforward, thanks to the seamless integration facilitated by Kubernetes. Here are the steps to kickstart your journey:
 1. **Qdrant Hybrid Cloud Activation**: Start by activating ‘Hybrid Cloud’ in your Qdrant Cloud account.
 2. **Cluster Integration**: Add your STACKIT Kubernetes clusters as a private region in the Hybrid Cloud section.
 3. **Effortless Deployment**: Use the Qdrant Management Console to effortlessly create and manage your Qdrant clusters on STACKIT.
 We invite you to explore the detailed documentation on deploying Qdrant on STACKIT, designed to guide you through each step of the process seamlessly.
 **> View Documentation**
 Learn more about Qdrant Hybrid Cloud in the official release blog. Ready to get started? Create your Qdrant Hybrid Cloud cluster in a few minutes by creating your Qdrant Cloud account.
@@ -0,0 +1,57 @@
 ---
 draft: false
 title: "Vultr and Qdrant Hybrid Cloud"
 short_description: "Qdrant Hybrid Cloud and Vultr Provide A Flexible Platform For High-Performance Vector Search For Next-Gen AI Workloads." 
 description: "Qdrant Hybrid Cloud and Vultr Provide A Flexible Platform For High-Performance Vector Search For Next-Gen AI Workloads."
 preview_image: /blog/hybrid-cloud-vultr/hybrid-cloud-vultr.png
 date: 2024-04-10T00:08:00Z
 author: Qdrant
 featured: false
 tags:
  - Qdrant
  - Vector Database
 ---
 ## Qdrant Hybrid Cloud and Vultr Provide A Flexible Platform For High-Performance Vector Search For Next-Gen AI Workloads
 We’re excited to share that Qdrant and Vultr are partnering to provide seamless scalability and performance for vector search workloads. With Vultr's global footprint and customizable platform, deploying vector search workloads becomes incredibly flexible. Qdrant's new Qdrant Hybrid Cloud offering and its Kubernetes-native design, coupled with Vultr's straightforward virtual machine provisioning, allows for simple setup when prototyping and building next-gen AI apps.
 ## Adapting to Diverse AI Development Needs with Customization and Deployment Flexibility
 In the fast-paced world of AI and ML, businesses are eagerly integrating AI and generative AI to enhance their products with new features like AI assistants, develop new innovative solutions, and streamline internal workflows with AI-driven processes. Given the diverse needs of these applications, it's clear that a one-size-fits-all approach doesn't apply to AI development. This variability in requirements underscores the need for adaptable and customizable development environments.
 Recognizing this, Qdrant and Vultr have teamed up to offer developers unprecedented flexibility and control. The collaboration enables the deployment of a fully managed vector database on Vultr’s adaptable platform, catering to the specific needs of diverse AI projects. This unique setup offers developers the ideal Vultr environment for their vector search workloads. It ensures seamless adaptability and data privacy with all data residing in their environment. For the first time, Qdrant Hybrid Cloud allows for fully managing a vector database on Vultr, promoting rapid development cycles without the hassle of modifying existing setups and ensuring that data remains secure within the organization. Moreover, this partnership empowers developers with centralized management over their vector database clusters via Qdrant’s control plane, enabling precise size adjustments based on workload demands. This joint setup marks a significant step in providing the AI and ML field with flexible, secure, and efficient application development tools.
 "Our collaboration with Qdrant empowers developers to unlock the potential of vector search applications, such as RAG, by deploying Qdrant Hybrid Cloud with its high-performance search capabilities directly on Vultr's global, automated cloud infrastructure. This partnership creates a highly scalable and customizable platform, uniquely designed for deploying and managing AI workloads with unparalleled efficiency." Kevin Cochrane, Vultr CMO.
 ## The Benefits of Deploying Qdrant Hybrid Cloud on Vultr
 Together, Qdrant Hybrid Cloud and Vultr offer enhanced AI and ML development with streamlined benefits:
 - **Simple and Flexible Deployment:** Deploy Qdrant Hybrid Cloud on Vultr in a few minutes with a simple “one-click” installation by adding your Vutlr environment as a private region to Qdrant.
 - **Scalability and Customizability**: Qdrant’s efficient data handling and Vultr’s scalable infrastructure means projects can be adjusted dynamically to workload demands, optimizing costs without compromising performance or capabilities.
 - **Unified AI Stack Management:** Seamlessly manage the entire lifecycle of AI applications, from vector search with Qdrant Hybrid Cloud to deployment and scaling with the Vultr platform and its AI and ML solutions, all within a single, integrated environment. This setup simplifies workflows, reduces complexity, accelerates development cycles, and simplifies the integration with other elements of the AI stack like model development, finetuning, or inference and training.
 - **Global Reach, Local Execution**: With Vultr's worldwide infrastructure and Qdrant's fast vector search, deploy AI solutions globally while ensuring low latency and compliance with local data regulations, enhancing user satisfaction.
 ## Getting Started with Qdrant Hybrid Cloud and Vultr
 ![hybrid-cloud-vultr-tutorial](/blog/hybrid-cloud-vultr/hybrid-cloud-vultr-tutorial.png)
 We've compiled an in-depth guide for leveraging Qdrant Hybrid Cloud on Vultr to kick off your journey into building cutting-edge AI solutions. For further insights into the deployment process, refer to our comprehensive documentation.
 1. **Tutorial Crafting a Personalized AI Assistant with RAG**
 > This tutorial outlines creating a personalized AI assistant using Qdrant Hybrid Cloud on Vultr, incorporating advanced vector search to power dynamic, interactive experiences. We will develop a RAG pipeline powered by DSPy and detail how to maintain data privacy within your Vultr environment.
 > 
 > 
 > **> Explore Tutorial**
 > 
 1. **Documentation: Effortless Deployment with Qdrant**
 > Our Kubernetes-native framework simplifies the deployment of Qdrant Hybrid Cloud on Vultr, enabling you to get started in just a few straightforward steps. Dive into our documentation to learn more.
 > 
 > 
 > **> View Documentation**
 > 
 Learn more about Qdrant Hybrid Cloud in the official release blog. Ready to get started? Create your Qdrant Hybrid Cloud cluster in a few minutes by creating your Qdrant Cloud account.