--- title: What Is Edge AI? Edge Computing Examples and Benefits description: Edge AI runs AI inference on or near devices instead of in the cloud, requiring the model, runtime, and data to live locally on phones, sensors, kiosks, or... canonical: https://daily.dev/posts/what-is-edge-ai-edge-computing-examples-and-benefits-jslvlcuol twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Is Edge AI? Edge Computing Examples and Benefits | daily.dev og:description: Edge AI runs AI inference on or near devices instead of in the cloud, requiring the model, runtime, and data to live locally on phones, sensors, kiosks, or... og:url: https://daily.dev/posts/what-is-edge-ai-edge-computing-examples-and-benefits-jslvlcuol og:image: https://api.daily.dev/og/posts/jSLVlCuol.png og:image:alt: What Is Edge AI? Edge Computing Examples and Benefits og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What Is Edge AI? Edge Computing Examples and Benefits **[Couchbase](https://daily.dev/sources/couchbase)** · 13 min read · 0 upvotes · 0 comments ## Summary Edge AI runs AI inference on or near devices instead of in the cloud, requiring the model, runtime, and data to live locally on phones, sensors, kiosks, or edge servers. The workflow trains models in the cloud, then compresses and deploys them for local inference, with hardware like NPUs and mobile GPUs from Qualcomm, Apple, and NVIDIA enabling this. Benefits include low latency, privacy, offline operation, and bandwidth savings, with use cases spanning retail, mobile, IoT, industrial, healthcare, and automotive. A dedicated section explains what edge AI needs from its data layer - local storage for RAG, sub-millisecond reads/writes, always-on offline operation, cloud-to-edge sync, and edge security/governance - followed by a walkthrough of how Couchbase Lite, Mobile, Edge Server, and Capella address each requirement. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is the difference between edge AI and on-device AI? On-device AI is a subset of edge AI where the model runs entirely on the end device with no dependency on a nearby server or gateway. Edge AI is the broader category that also includes nearby edge servers and gateways processing data from multiple devices. All on-device AI counts as edge AI, but not all edge AI is on-device. _Weighing on-device versus broader edge deployment options is easier with real comparisons surfaced on daily.dev._ ### What database features does an edge AI application need for local RAG? It needs an embedded database that operates fully offline, serves sub-millisecond queries from local storage, and performs vector search for retrieval-augmented generation without a network connection, while syncing bidirectionally with the cloud and resolving conflicts automatically. Couchbase Lite is built for this, combining local storage, vector search, SQL++ queries, and cloud sync in one embedded NoSQL library for mobile and IoT. _Developers picking a data layer for offline RAG can compare embedded database options through daily.dev._ ### How does edge AI differ from cloud AI in terms of latency and cost? Edge AI runs inference on-device, gateway, or edge server with sub-millisecond to low-millisecond latency and can operate fully offline, while cloud AI adds tens to hundreds of milliseconds of network round-trip and requires a stable connection. Edge AI has upfront hardware costs with lower ongoing egress costs, whereas cloud AI incurs ongoing compute, API, storage, and transfer costs. _Comparing edge versus cloud AI trade-offs is simpler when architecture breakdowns land in your daily.dev feed._ ## Similar posts on daily.dev - [Edge AI explained](https://daily.dev/posts/edge-ai-explained-h5ibas7ka) · Serokell · 0 upvotes · 0 comments - [On-Device AI: Benefits, Use Cases, and Challenges](https://daily.dev/posts/on-device-ai-benefits-use-cases-and-challenges-3u9tembll) · Couchbase · 0 upvotes · 0 comments - [Medium](https://daily.dev/posts/medium-hqgq1rgho) · Medium · 0 upvotes · 0 comments - [Edge AI: The future of AI inference is smarter local compute](https://daily.dev/posts/edge-ai-the-future-of-ai-inference-is-smarter-local-compute-pf1zicrmv) · InfoWorld · 0 upvotes · 0 comments - [Why edge computing isn’t just cloud at the network edge](https://daily.dev/posts/why-edge-computing-isn-t-just-cloud-at-the-network-edge-8e8bvl6mn) · All Things Open · 1 upvotes · 0 comments --- Tags: [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#edge-computing](https://daily.dev/tags/edge-computing), [#couchbase](https://daily.dev/tags/couchbase) [View this post on daily.dev](https://daily.dev/posts/what-is-edge-ai-edge-computing-examples-and-benefits-jslvlcuol) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"What Is Edge AI? 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