Reliable product-event delivery without workflow graphs or instance operations.
Quick take
Product-event delivery should not require a workflow per path. Meshes makes fan-out, recovery, customer isolation, and delivery history part of the platform contract.
Focused delivery
Your SaaS emits lifecycle events that need to reach customer-owned CRMs, email tools, and webhooks with retries, optional ingestion idempotency, replay, and workspace isolation built in.
Managed operations
Meshes owns the delivery path and its recovery behavior. Your team configures connections and rules instead of operating an instance and maintaining workflow executions for every destination.
Customer operations
Each customer manages connections and routing rules in an isolated workspace, while your team can inspect destination outcomes and recover eligible failures without tracing workflow runs.
The architecture question
Meshes makes fan-out, retry isolation, replay, and customer-scoped history platform defaults instead of workflow design decisions.
Meshes
Your app sends an event once. Meshes fans it out to every configured destination, retries failures, captures dead letters, and logs delivery status per destination. There is no workflow canvas because there is no workflow to build.
n8n
The equivalent path uses a webhook trigger plus destination nodes, credentials, branches, retry decisions, and execution monitoring that your team models and operates as workflow logic.
The Meshes advantage: every customer connection and destination attempt stays visible in one delivery model, without operating a workflow instance or duplicating recovery logic.
What you maintain
With n8n (self-hosted)
You run the n8n instance, build a workflow for each integration, monitor failures in the n8n UI, manage credentials, and maintain the infrastructure that keeps it all running.
With n8n Cloud
n8n manages the instance. You still build workflows per integration path, own the retry and execution design inside those workflows, and manage credentials and monitoring across them.
With Meshes
You make one API call. Meshes handles fan-out, retries with exponential backoff and jitter, dead letter capture, replay, and per-destination delivery history. Each new destination is a connection and a rule, not a workflow to build and maintain.
Meshes delivery advantages
| Capability | Meshes | n8n |
|---|---|---|
| Architecture | ||
| Built for | Event delivery to SaaS integrations | Workflow orchestration between systems |
| How it works | Your app sends events via API or SDK | Triggers fire workflows with sequential or branched steps |
| Embedded delivery operations | Focused customer workspace for connections, rules, mappings, and history | A separate Embed license exposes the broader workflow and credential model |
| Reliability and delivery | ||
| Automatic retries | Exponential backoff with jitter, built in | Execution retries and failure handling live in workflow design |
| Ingestion idempotency | Optional idempotency keys prevent duplicate event ingestion | Duplicate prevention depends on workflow and destination design |
| Dead letter capture | Dedicated failed-delivery state and replay path | Failed executions remain workflow-level records |
| Event replay | Replay failed deliveries per destination | Re-run workflow executions manually |
| Fan-out routing | One event to multiple destinations in parallel | One trigger starts a workflow; fan-out requires branches or multiple workflows |
| Developer experience | ||
| SDKs | Node.js and Go | Webhook triggers, app nodes, or custom node development |
| Delivery observability | Per-destination event history, failure details, and replay | Per-execution logs inside each workflow |
| Credential model | Per-workspace customer connections managed by Meshes | Credentials attached to workflows, nodes, or shared n8n credentials |
| Commercial model | Priced around event volume and workspaces | Self-hosted infrastructure you operate or cloud execution-based pricing |
Architecture
Meshes
Event delivery to SaaS integrationsn8n
Workflow orchestration between systemsMeshes
Your app sends events via API or SDKn8n
Triggers fire workflows with sequential or branched stepsMeshes
Focused customer workspace for connections, rules, mappings, and historyn8n
A separate Embed license exposes the broader workflow and credential modelReliability and delivery
Meshes
Exponential backoff with jitter, built inn8n
Execution retries and failure handling live in workflow designMeshes
Optional idempotency keys prevent duplicate event ingestionn8n
Duplicate prevention depends on workflow and destination designMeshes
Dedicated failed-delivery state and replay pathn8n
Failed executions remain workflow-level recordsMeshes
Replay failed deliveries per destinationn8n
Re-run workflow executions manuallyMeshes
One event to multiple destinations in paralleln8n
One trigger starts a workflow; fan-out requires branches or multiple workflowsDeveloper experience
Meshes
Node.js and Gon8n
Webhook triggers, app nodes, or custom node developmentMeshes
Per-destination event history, failure details, and replayn8n
Per-execution logs inside each workflowMeshes
Per-workspace customer connections managed by Meshesn8n
Credentials attached to workflows, nodes, or shared n8n credentialsMeshes
Priced around event volume and workspacesn8n
Self-hosted infrastructure you operate or cloud execution-based pricingImplementation
Same event, different approach. One is a delivery call. The other is a workflow definition.
Meshes
import MeshesEventsClient from "@mesheshq/events";
const meshes = new MeshesEventsClient(
process.env.WORKSPACE_PUBLISHABLE_KEY!,
);
await meshes.emit({
event: "user.signup",
payload: {
email: user.email,
plan: user.plan,
source: "website",
},
});n8n
await fetch("https://your-n8n.example.com/webhook/user-signup", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({ email, plan, source }),
});
// Then inside n8n you build the workflow:
// - Webhook trigger node
// - HubSpot node
// - Salesforce node
// - Mailchimp node
// - Slack node
// - branching or code nodes when needed
//
// The delivery path now depends on workflow
// credentials, branches, and execution state.Four downstream systems usually mean either one larger orchestration graph with branches and credentials, or multiple webhook-triggered workflows to own and monitor.
When the job is "deliver this event to four systems reliably," Meshes replaces the workflow you would otherwise build and maintain. Product-event fan-out stays one customer-scoped delivery flow instead of becoming workflow logic and per-instance operations.
Why engineering teams choose Meshes
Meshes does one thing: get product events to downstream systems reliably. No canvas, no step editor, and no branching logic to maintain when the event just needs to land.
Exponential backoff, jitter, dead letter capture, and replay are delivery defaults, not branches or retry handlers you recreate in each workflow.
n8n starts workflows. Meshes fans one event out to every configured destination in parallel so your delivery model does not grow into an orchestration graph.
Give customers a white-label workspace where they connect their own HubSpot, Salesforce, or Slack accounts. Meshes is built for customer-facing connection ownership.
Search by event, inspect status per destination, see failures, and replay without jumping across separate workflow runs or execution views.
Connections, rules, mappings, retries, and delivery history stay in the same customer-scoped delivery layer instead of handing product traffic into another workflow system.
Common questions