Akamai Sharpens Its AI Edge with Launch of Akamai Cloud Inference
Akamai (NASDAQ: AKAM) has launched Akamai Cloud Inference, a new service that delivers significant improvements in AI inference performance. The solution offers 3x better throughput, up to 60% less latency, and 86% cost savings compared to traditional hyperscale infrastructure.
Running on Akamai Cloud's distributed platform with over 4,200 points of presence across 1,200+ networks in 130+ countries, the service includes advanced compute capabilities, data management through partnerships with VAST Data, containerization via Linode Kubernetes Engine-Enterprise, and edge compute features with WebAssembly capabilities.
The platform specifically targets the growing need for efficient AI inference processing at the edge, where real-time decision-making is crucial. Early implementations include in-car voice assistance, AI-powered crop management, image optimization, virtual shopping experiences, and customer feedback analysis.
Akamai (NASDAQ: AKAM) ha lanciato Akamai Cloud Inference, un nuovo servizio che offre miglioramenti significativi nelle prestazioni di inferenza AI. La soluzione garantisce un throughput 3 volte migliore, fino a 60% di latenza in meno e risparmi del 86% rispetto all'infrastruttura tradizionale hyperscale.
Funzionante sulla piattaforma distribuita di Akamai Cloud, con oltre 4.200 punti di presenza in più di 1.200 reti in oltre 130 paesi, il servizio include capacità di calcolo avanzate, gestione dei dati attraverso partnership con VAST Data, containerizzazione tramite Linode Kubernetes Engine-Enterprise e funzionalità di calcolo edge con capacità WebAssembly.
La piattaforma si rivolge specificamente alla crescente necessità di un'elaborazione efficiente dell'inferenza AI al confine, dove il processo decisionale in tempo reale è cruciale. Le prime implementazioni includono assistenza vocale in auto, gestione delle colture alimentata dall'AI, ottimizzazione delle immagini, esperienze di shopping virtuale e analisi del feedback dei clienti.
Akamai (NASDAQ: AKAM) ha lanzado Akamai Cloud Inference, un nuevo servicio que ofrece mejoras significativas en el rendimiento de la inferencia de IA. La solución proporciona 3 veces mejor rendimiento, hasta 60% menos de latencia y ahorros del 86% en comparación con la infraestructura hyperscale tradicional.
Funcionando en la plataforma distribuida de Akamai Cloud, con más de 4,200 puntos de presencia en más de 1,200 redes en más de 130 países, el servicio incluye capacidades de computación avanzadas, gestión de datos a través de asociaciones con VAST Data, contenedorización mediante Linode Kubernetes Engine-Enterprise y características de computación en el borde con capacidades de WebAssembly.
La plataforma se dirige específicamente a la creciente necesidad de un procesamiento eficiente de la inferencia de IA en el borde, donde la toma de decisiones en tiempo real es crucial. Las primeras implementaciones incluyen asistencia de voz en el automóvil, gestión de cultivos impulsada por IA, optimización de imágenes, experiencias de compras virtuales y análisis de retroalimentación de clientes.
Akamai (NASDAQ: AKAM)는 Akamai Cloud Inference를 출시했습니다. 이 새로운 서비스는 AI 추론 성능에서 상당한 개선을 제공합니다. 이 솔루션은 전통적인 하이퍼스케일 인프라에 비해 3배 더 나은 처리량, 최대 60% 낮은 대기 시간, 86% 비용 절감을 보장합니다.
130개 이상의 국가에 걸쳐 1,200개 이상의 네트워크에 4,200개 이상의 존재 지점이 있는 Akamai Cloud의 분산 플랫폼에서 운영되며, 이 서비스는 고급 컴퓨팅 기능, VAST Data와의 파트너십을 통한 데이터 관리, Linode Kubernetes Engine-Enterprise를 통한 컨테이너화, WebAssembly 기능을 갖춘 엣지 컴퓨팅 기능을 포함합니다.
이 플랫폼은 실시간 의사결정이 중요한 엣지에서 효율적인 AI 추론 처리의 증가하는 필요성에 특별히 초점을 맞추고 있습니다. 초기 구현에는 자동차 내 음성 지원, AI 기반 작물 관리, 이미지 최적화, 가상 쇼핑 경험 및 고객 피드백 분석이 포함됩니다.
Akamai (NASDAQ: AKAM) a lancé Akamai Cloud Inference, un nouveau service qui offre des améliorations significatives des performances d'inférence de l'IA. La solution propose 3 fois meilleur débit, jusqu'à 60 % de latence en moins et 86 % d'économies de coûts par rapport à l'infrastructure hyperscale traditionnelle.
Fonctionnant sur la plateforme distribuée d'Akamai Cloud, avec plus de 4 200 points de présence à travers plus de 1 200 réseaux dans plus de 130 pays, le service comprend des capacités de calcul avancées, la gestion des données grâce à des partenariats avec VAST Data, la conteneurisation via Linode Kubernetes Engine-Enterprise et des fonctionnalités de calcul en périphérie avec des capacités WebAssembly.
La plateforme cible spécifiquement le besoin croissant d'un traitement efficace de l'inférence IA en périphérie, où la prise de décision en temps réel est cruciale. Les premières mises en œuvre incluent l'assistance vocale dans les voitures, la gestion des cultures alimentée par l'IA, l'optimisation des images, les expériences de shopping virtuel et l'analyse des retours clients.
Akamai (NASDAQ: AKAM) hat Akamai Cloud Inference gestartet, einen neuen Dienst, der erhebliche Verbesserungen in der AI-Inferenzleistung bietet. Die Lösung bietet 3x bessere Durchsatzraten, bis zu 60% weniger Latenz und 86% Kostenersparnis im Vergleich zur traditionellen Hyperscale-Infrastruktur.
Die Plattform läuft auf der verteilten Plattform von Akamai Cloud mit über 4.200 Präsenzpunkten in mehr als 1.200 Netzwerken in über 130 Ländern und umfasst fortschrittliche Rechenkapazitäten, Datenmanagement durch Partnerschaften mit VAST Data, Containerisierung über Linode Kubernetes Engine-Enterprise und Edge-Computing-Funktionen mit WebAssembly-Funktionen.
Die Plattform zielt speziell auf den wachsenden Bedarf an effizienter AI-Inferenzverarbeitung am Edge ab, wo Echtzeit-Entscheidungen entscheidend sind. Zu den frühen Implementierungen gehören Sprachassistenz im Auto, AI-gestützte Pflanzenmanagement, Bildoptimierung, virtuelle Einkaufserlebnisse und Kundenfeedback-Analyse.
- Significant cost reduction of 86% compared to traditional infrastructure
- 3x throughput improvement and 60% latency reduction
- Extensive global infrastructure with 4,200+ points of presence
- Strategic partnerships with major tech providers (Nvidia, VAST Data)
- Early customer adoption across diverse use cases
- Faces competition from established hyperscale cloud providers
- Requires significant ongoing investment in infrastructure
Insights
Akamai's Cloud Inference launch represents a significant technical advancement in the AI deployment landscape. The architectural approach leverages Akamai's massive distributed network—4,200+ points of presence across 1,200+ networks in 130+ countries—to position AI inference workloads closer to end users and data sources.
The performance claims are substantial:
What's technically compelling is the comprehensive stack Akamai has assembled. Their integration with NVIDIA's AI Enterprise ecosystem optimizes GPU performance, while partnerships with VAST Data and vector database vendors Aiven and Milvus enable efficient data management. The Kubernetes implementation with LKE-Enterprise provides the orchestration layer for deploying and scaling inference workloads, while WebAssembly support enables lightweight edge execution.
This approach solves a critical technical challenge in AI deployment: while foundation model training requires massive centralized computing resources, inference—especially for time-sensitive applications—benefits tremendously from distributed execution. As AI shifts from novelty to utility, this architectural distinction becomes increasingly valuable, particularly for real-time applications like in-vehicle assistance, automated visual processing, and operational intelligence.
Akamai's launch of Cloud Inference represents a strategic expansion beyond its traditional CDN and security services into the high-growth edge AI market. This positions Akamai to capitalize on a critical industry shift: as AI moves from training to inference, computing needs are becoming more distributed rather than centralized.
The business rationale is compelling. Akamai's existing distributed network—built over 25 years—provides a ready-made infrastructure advantage that typical hyperscalers can't easily replicate. By claiming
The market timing is opportune. As the article notes, enterprises are increasingly recognizing that the initial LLM hype created distractions from practical AI solutions. Companies are now focusing on lightweight, purpose-built AI models that deliver specific business outcomes rather than general-purpose capabilities. This aligns perfectly with Akamai's edge-focused offering.
The early customer examples cited—in-car voice assistance, AI crop management, image optimization, virtual shopping experiences—highlight the diversity of potential applications. This suggests Akamai could penetrate multiple verticals rather than being confined to specific industry segments. By focusing on the operational phase of AI rather than training, Akamai is targeting the larger, more sustainable portion of the AI value chain where continuous usage generates recurring revenue streams.
New service gives companies the ability to realize a 3x improvement in throughput,
"Getting AI data closer to users and devices is hard, and it's where legacy clouds struggle," said Adam Karon, Chief Operating Officer and General Manager, Cloud Technology Group at Akamai. "While the heavy lifting of training LLMs will continue to happen in big hyperscale data centers, the actionable work of inferencing will take place at the edge where the platform Akamai has built over the past two and a half decades becomes vital for the future of AI and sets us apart from every other cloud provider in the market."
AI inference on Akamai Cloud
Akamai's new solution provides tools for platform engineers and developers to build and run AI applications and data-intensive workloads closer to end users, delivering 3x better throughput while reducing latency up to 2.5x. Using Akamai's solution, businesses can save up to
- Compute: Akamai Cloud offers a versatile compute arsenal, from classic CPUs for fine-tuned inference, to powerful accelerated-compute options in GPUs, and tailored ASIC VPUs to provide the right horsepower for a spectrum of AI inference challenges. Akamai integrates with Nvidia's AI Enterprise ecosystem, leveraging Triton, TAO Toolkit, TensorRT, and NVFlare to optimize performance of AI inference on NVIDIA GPUs.
- Data management: Akamai enables customers to unlock the full potential of AI inference with a cutting-edge data fabric purpose-built for modern AI workloads. Akamai has partnered with VAST Data to provide streamlined access to real-time data to accelerate inference-related tasks, essential to delivering relevant results and a responsive experience. This is complemented by highly scalable object storage to manage the volume and variety of datasets critical to AI applications, and integration with leading vector database vendors, including Aiven and Milvus, to enable retrieval-augmented generation (RAG). With this data management stack, Akamai securely stores fine-tuned model data and training artifacts to deliver low-latency AI inference at global scale.
- Containerization: Containerizing AI workloads enables demand-based autoscaling, improved application resilience, and hybrid/multicloud portability, while optimizing both performance and cost. With Kubernetes, Akamai delivers faster, cheaper, and more secure AI inference at petabyte-scale performance. Underpinned by Linode Kubernetes Engine (LKE)-Enterprise, a new enterprise edition of Akamai Cloud's Kubernetes orchestration platform designed specifically for large-scale enterprise workloads, and the recently announced Akamai App Platform, Akamai Cloud Inference is able to quickly deploy an AI-ready platform of open source Kubernetes projects, including KServe, Kubeflow, and SpinKube, seamlessly integrated to streamline the deployment of AI models for inference.
- Edge compute: To simplify how developers build AI-powered applications, Akamai AI Inference includes WebAssembly (Wasm) capabilities. Working with Wasm providers like Fermyon, Akamai enables developers to execute inferencing for LLMs directly from serverless apps, allowing customers to execute lightweight code at the edge to enable latency-sensitive applications.
Together, these tools create a powerful platform for low-latency, AI-powered applications that allows companies to deliver the experience their users demand. Akamai Cloud Inference runs on the company's massively distributed platform capable of consistently delivering over one petabyte per second of throughput for data-intensive workloads. Comprising more than 4,200 points of presence across greater than 1,200 networks in over 130 countries worldwide, Akamai Cloud makes compute resources available from cloud to edge while accelerating application performance and increasing scalability.
The shift from training to inference
As AI adoption matures, enterprises are recognizing that the hype around LLMs has created a distraction, drawing focus away from practical AI solutions better suited to solve specific business problems. LLMs excel at general-purpose tasks like summarization, translation, and customer service. These are very large models that are expensive and time-consuming to train. Many enterprises have found themselves constrained by architectural and cost requirements, including data center and computational power; well-structured, secure, and scalable data systems; and the challenges that location and security requirements place on decision latency. Lightweight AI models, — designed to address specific business problems — can be optimized for individual industries, can use proprietary data to create measurable outcomes, and represent a better return on investment for enterprises today.
AI inference needs a more distributed cloud
Increasingly, data will be generated outside of centralized data centers or cloud regions. This shift is driving demand for AI solutions that leverage data generation closer to the point of origin. This fundamentally reshapes infrastructure needs as enterprises move beyond building and training LLMs, toward using data for faster, smarter decisions and investing in more personalized experiences. Enterprises recognize that they can generate more value by leveraging AI to manage and improve their business operations and processes. Distributed cloud and edge architectures are emerging as preferable for operational intelligence use cases because they can provide real-time, actionable insights across distributed assets even in remote environments. Early customer examples on Akamai Cloud include in-car voice assistance, AI-powered crop management, image optimization for consumer product marketplaces, virtual garment visualization shopping experiences, automated product description generators, and customer feedback sentiment analyzers.
"Training an LLM is like creating a map, requiring you to gather data, analyze terrain, and plot routes. It's slow and resource-intensive, but once built, it's highly useful. AI inference is like using a GPS, instantly applying that knowledge, recalculating in real time, and adapting to changes to get you where you need to go," explained Karon. "Inference is the next frontier for AI."
About Akamai
Akamai is the cybersecurity and cloud computing company that powers and protects business online. Our market-leading security solutions, superior threat intelligence, and global operations team provide defense in depth to safeguard enterprise data and applications everywhere. Akamai's full-stack cloud computing solutions deliver performance and affordability on the world's most distributed platform. Global enterprises trust Akamai to provide the industry-leading reliability, scale, and expertise they need to grow their business with confidence. Learn more at akamai.com and akamai.com/blog, or follow Akamai Technologies on X and LinkedIn.
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SOURCE Akamai Technologies, Inc.
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