Agent-native edge caching

Caching for AI agents: faster, cheaper, visible.

Offload repetitive agent traffic at the edge to reduce latency and inference costs with a lightweight integration.

Request path

Illustrative cache behavior

Agent request

chat.completions.create()

Request

Edge cache

Check for a reusable response

Cache hit

Model provider

Run only when no reusable response is found

Skipped
Reuse repeated work while keeping cache behavior observable.

Multi-layer caching

Serve each request from the right layer.

From edge CDNs to regional Redis and local memory, Alchymos routes agent traffic to the fastest available layer.

Selected layer · CDN edge

Serve common, read-heavy responses close to users for low-latency global access.

A lightweight integration

Add caching to the clients you already use.

Connect an existing OpenAI client and keep working with familiar APIs. Start with the SDK, then configure the caching behavior that fits your workflow.

See SDK documentation
TypeScript
import OpenAI from "openai";
import { Alchymos } from "@alchymos/openai";

const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const alchymos = new Alchymos(process.env.ALCHYMOS_API_KEY);

alchymos.withLlm(openai);

const response = await openai.chat.completions.create(params);

Built for control

Caching that fits your workflow.

Choose how requests are scoped, routed, inspected, and refreshed.

Global edge distribution

Serve cached responses from the nearest region to your user.

Authenticated caching

Scope cached data to organizations, licenses, or individual users.

Fine-grained rules

Configure behavior by tool, parameters, or request type.

Automatic invalidation

Purge entries when upstream data changes.

Purge API

Clear cache entries manually or programmatically.

Metrics and analytics

Review cache hits, latency, and tokens saved.

Cache debugging

Inspect headers to understand why requests are cached or bypassed.

Performance controls

Set performance targets for enterprise workloads.

Explore the SDK to see integration examples, or talk with us about caching for your agent workflows.