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Merge pull request #1819 from qdrant/add-edge-beta-page
Added Edge Beta page
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m-qdrant
@@ -4,7 +4,7 @@ label:
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title: Qdrant Cloud Inference
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icon:
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src: /icons/fill/cloud-system-purple.svg
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alt: Privacy and Data Sovereignty
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alt: Cloud system
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description: Qdrant Cloud Inference lets you generate and store text and image embeddings directly within your managed Qdrant Cloud cluster, eliminating external pipelines and supporting multimodal and hybrid search from a single API.
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startFree:
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text: Get Started
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@@ -0,0 +1,13 @@
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---
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title: Edge beta
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description: Edge beta
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url: edge
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aliases: [edge-beta, edge-beta/]
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build:
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render: always
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cascade:
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- build:
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list: local
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publishResources: false
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render: never
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---
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@@ -0,0 +1,17 @@
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---
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title: FAQs
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questions:
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- id: 0
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question: Who is Qdrant Edge for?
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answer: Teams building AI systems that need fast, local vector search on embedded or resource-constrained devices, such as robots, mobile apps, or IoT hardware.
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- id: 1
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question: Is this available to all Qdrant users?
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answer: Not yet. Qdrant Edge is in private beta. We're selecting a limited number of partners based on technical fit and active edge deployment scenarios.
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- id: 2
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question: What are the minimum requirements to join the beta?
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answer: You should have a clear use case for on-device or offline vector search. Preference is given to companies working with embedded hardware or deploying agents at the edge.
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- id: 3
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question: How do I get access?
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answer: Qdrant Edge is currently in private beta. If you're building edge-native or embedded AI systems and want early access, apply to join the beta.
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sitemapExclude: true
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---
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@@ -0,0 +1,35 @@
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---
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title: Real-time vector retrieval for Edge AI in resource-constrained environments
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features:
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- id: 0
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image:
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src: /img/edge-beta-features/native-vector.svg
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alt: Native Vector Search
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title: Native Vector Search for Embedded & Edge AI
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description: Runs as a lightweight, in-process library. No background threads, no services - ideal for mobile, robotic, and embedded environments.
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- id: 1
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image:
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src: /img/edge-beta-features/optimized-for-low-memory.svg
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alt: Low-Memory
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title: Optimized for Low-Memory, Low-Compute Devices
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description: Dramatically Designed for resource-constrained hardware. No idle overhead, no runtime daemons. Fits into tightly scoped edge deployments. memory usage with built-in compression options and offload data to disk.
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- id: 2
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image:
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src: /img/edge-beta-features/local-by-default.svg
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alt: Local by Default
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title: Local by Default, Cloud-Connected When Needed
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description: Retrieval runs fully offline. Sync with Qdrant Cloud only when required - for data transfer, tenant promotion, or coordination at scale.
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- id: 3
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image:
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src: /img/edge-beta-features/hybrid-and-multimodal-search.svg
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alt: Hybrid & Multimodal Search
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title: Hybrid & Multimodal Search On-Device
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description: Supports dense and multimodal vectors with structured filtering. Enables real-time retrieval from text, image, audio, or sensor-derived embeddings.
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- id: 4
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image:
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src: /img/edge-beta-features/multitenancy-built.svg
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alt: Multitenancy Built
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title: Edge-Scale Multitenancy with Native SDKs
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description: Supports payload- and shard-based tenant isolation. Routes queries across uneven edge workloads. Native SDKs in Java (Android), Swift (Apple), and more.
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sitemapExclude: true
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---
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@@ -0,0 +1,14 @@
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---
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title: Apply to Join the Beta
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description: Private beta available to selected teams building embedded or edge-native AI systems.
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form:
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id: edge-beta-form
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hubspotFormOptions: '{
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"region": "eu1",
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"portalId": "139603372",
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"formId": "3adfb3a8-1c4b-4670-958f-325826039f7e",
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"submitButtonClass": "button button_contained",
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}'
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sitemapExclude: true
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---
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@@ -0,0 +1,12 @@
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---
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title: Apply to Join the Beta
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button:
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url: "#form"
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text: Apply Now
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target: "self"
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image:
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src: /img/rocket.svg
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alt: Rocket
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sitemapExclude: true
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---
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@@ -0,0 +1,18 @@
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---
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title: Qdrant Edge
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label:
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title: Edge AI Infrastructure
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icon:
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src: /icons/fill/edge-blue.svg
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alt: Qdrant edge
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subtitle: Run Vector Search Inside Embedded and Edge AI Systems
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description: Qdrant Edge is a lightweight, in-process vector search engine designed for embedded devices, autonomous systems, and mobile agents. It enables on-device retrieval with minimal memory footprint, no background services, and optional synchronization with Qdrant Cloud.
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startFree:
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text: Apply to Join the Beta
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url: "#form"
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image:
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src: /img/qdrant-edge-scheme.svg
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alt: Qdrant edge scheme
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sitemapExclude: true
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---
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@@ -0,0 +1,29 @@
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---
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title: Purpose-Built for On-Device AI Workloads
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cards:
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- id: 0
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icon:
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src: /img/edge-beta-vectors/icon1.svg
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alt: Robotics & Autonomy
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title: Robotics & Autonomy
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description: Run multimodal retrieval from onboard sensors (like LiDAR, radar, and cameras) for real-time navigation and decision-making.
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- id: 1
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icon:
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src: /img/edge-beta-vectors/icon2.svg
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alt: Offline Voice Assistants
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title: Offline Voice Assistants
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description: Power local memory for privacy-first assistants on mobile or embedded hardware, without relying on a persistent connection.
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- id: 2
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icon:
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src: /img/edge-beta-vectors/icon3.svg
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alt: Smart Retail & Kiosks
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title: Smart Retail & Kiosks
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description: Enable product similarity and anomaly detection on edge terminals with limited or intermittent connectivity.
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- id: 3
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icon:
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src: /img/edge-beta-vectors/icon4.svg
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alt: Industrial IoT
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title: Industrial IoT
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description: Perform local retrieval and diagnostics from sensor-derived embeddings in air-gapped or bandwidth-constrained environments.
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sitemapExclude: true
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---
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@@ -39,6 +39,9 @@ menuItems:
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name: Qdrant Cloud Inference
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url: /cloud-inference/
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- id: 5
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name: Qdrant Edge (Private Beta)
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url: /edge/
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- id: 6
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name: Pricing
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url: /pricing/
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- title: Use Cases
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@@ -31,6 +31,10 @@ menuItems:
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name: Qdrant Cloud Inference
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icon: cloud-inference.svg
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url: /cloud-inference/
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- id: subMenu-0-5
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name: Qdrant Edge (Private Beta)
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icon: edge.svg
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url: /edge/
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# - id: subMenu-0-4
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# name: Private Cloud
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# icon: private-cloud.svg
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