Cache semantica: la base di un'IA più veloce

Fastly AI Accelerator

Ottieni migliori prestazioni IA con il caching intelligente che comprende i tuoi dati. AI Accelerator di Fastly aumenta le prestazioni di LLM popolari come OpenAI e Google Gemini di 9 volte. Non è necessaria alcuna ricostruzione, basta una riga di codice.

Prova e vedi

Perché i tuoi carichi di lavoro di IA hanno bisogno di un livello di cache

I carichi di lavoro di IA possono risultare oltre un ordine di grandezza più lenti rispetto all'elaborazione non LLM. I tuoi utenti sentono la differenza da decine di millisecondi a diversi secondi, e su migliaia di richieste la sentono anche i tuoi server.

La cache semantica mappa le query ai concetti come vettori, memorizzando le risposte alle domande indipendentemente da come vengano poste. È una buona pratica raccomandata dai principali fornitori di LLM e AI Accelerator rende la cache semantica più semplice.

Vantaggi

Elimina lo stress derivante dall'uso degli LLM e costruisci applicazioni più efficienti

Fastly AI Accelerator riduce le chiamate alle API e i costi grazie a una cache semantica intelligente.

Migliora le prestazioni

Fastly aiuta a rendere le API IA veloci e affidabili riducendo il numero di richieste e i tempi di richiesta con la cache semantica.
Ridurre i costi

Taglia i costi riducendo l'uso dell'API a monte, servendo i contenuti direttamente da Fastly cache.
Aumenta la produttività degli sviluppatori

Risparmia tempo prezioso agli sviluppatori ed evita di reinventare la ruota memorizzando le risposte dell'IA e sfruttando la potenza della piattaforma Fastly.

Frequently Asked Questions

What is Fastly’s AI Accelerator and how does it improve AI performance?

AI Accelerator is a semantic caching solution for large language model (LLM) APIs used in generative AI applications. AI request handling is positioned at the edge of the network, with the platform utilizing intelligent semantic caching and optimized delivery to ensure that organizations can provide faster AI responses to users. Fewer trips to the LLM API also results in savings on token costs.

How does Fastly enable AI acceleration at the edge?

Fastly enables AI acceleration by moving AI request handling, optimization, and response delivery closer to end users. Instead of routing every individual query back to a centralized, high-latency data center or LLM provider, Fastly’s global edge network optimizes traffic flow to significantly improve throughput and reduce round-trip times. This approach is especially effective for high-volume inference workloads where even millisecond delays can degrade the user experience.

What is semantic caching and how does Fastly optimize LLM costs?

Semantic caching is a technique that identifies and reuses similar or equivalent AI responses, rather than caching only exact matches. It breaks the query down into smaller, meaningful concepts, which can be used to understand matches against future queries — even though they are not identical, just semantically similar. Fastly applies semantic caching at the edge to reduce redundant LLM inference calls, lower token costs, and deliver consistently faster AI responses. This is particularly valuable for chatbots and virtual assistants, code generators, content creation tools, and knowledge bases.

How does Fastly improve LLM performance optimization?

The most critical performance metric for AI applications is how quickly a user sees a response. Traditional LLMs are computationally expensive and slow. Using semantic caching, Fastly can identify if a new query is essentially the same as a previous one. In these cases, Fastly serves the answer directly from the edge. This reduces the latency from seconds (waiting for the LLM to generate the response) to milliseconds (serving a pre-cached response), representing a massive performance improvement for the end user.

Can Fastly reduce infrastructure costs for AI applications?

Yes. By utilizing semantic caching, Fastly reduces the number of calls that need to reach backend LLM providers. This lowers inference costs, reduces origin load, and helps teams control spend as AI usage grows—without sacrificing response speed or user experience.

How does Fastly AI integrate with existing AI stacks and providers?

Fastly provides a high-performance delivery and optimization layer that sits seamlessly in front of an organization's existing AI infrastructure and LLM providers. Because it functions as a performance-enhancing proxy rather than a replacement for specific models, engineering teams can accelerate AI workloads without modifying their underlying frameworks, deployment pipelines, or specific model choices.

Is Fastly AI suitable for enterprise and production-grade AI workloads?

Yes. Fastly AI is built for enterprise-scale AI applications that demand reliability, security, and predictable performance. It provides the controls, observability, and scalability required by CTOs and platform leaders running AI workloads in production, while enabling faster AI experiences for end users globally.

What types of AI use cases benefit most from Fastly AI?

Fastly AI is well-suited for conversational AI and customer support, AI-powered search and knowledge bases, real-time personalization and content generation, and agentic workflows. Any application where LLM performance optimization and low-latency responses are critical can benefit from Fastly’s edge-based semantic caching capabilities.

Fastly aiuta a potenziare piattaforme LLM su scala web.

Fastly può aiutarti a ottimizzare la tua piattaforma LLM oggi stesso.

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