What is Expanso and how does it work?

Expanso is a managed platform for deploying intelligent data pipelines at the edge. It processes data where it's generated - reducing bandwidth, latency, and costs. You deploy lightweight agents on your infrastructure, build pipelines using our visual builder or YAML, and control everything from a central SaaS platform.

Can I run AI/ML models directly in my data pipelines?

Yes! Expanso supports running ONNX, TensorFlow Lite, and other models as native pipeline steps. Execute low-latency inference on streaming data, enrich events with model outputs (like risk scores), and make decisions at the edge without cloud round-trips.

How many pre-built components are available?

Expanso provides 200+ pre-built components including inputs (Kafka, HTTP, files), processors (transformations, filtering, PII masking, aggregations), and outputs (S3, Snowflake, Datadog, Splunk). Browse the complete catalog in our Component Reference.

Do I need to write code to build pipelines?

No - use our drag-and-drop visual pipeline builder to create sophisticated pipelines without code. For advanced use cases, you can also write pipelines in YAML or use the Bloblang transformation language for complex data mappings.

How does Expanso help with data governance and compliance?

Expanso includes built-in governance features: automatic PII detection and masking, policy enforcement at the edge, RBAC, SSO integration, and comprehensive audit trails. Mask sensitive data before it ever leaves your network.

types.StatusResponse

last_config_updatestring

local_modeboolean

namestring

node_idstring

orchestrator object

connectedboolean

last_seenstring

urlstring

pipelines object[]

Array [

idstring

namestring

statusstring

versioninteger

]

resources object

cpu_percentnumber

disk_percentnumber

goroutinesinteger

memory_percentnumber

start_timestring

statustypes.HealthStatusType (string)

Possible values: [healthy, degraded, unhealthy]

uptimestring

versionstring

types.StatusResponse
{
  "last_config_update": "string",
  "local_mode": true,
  "name": "string",
  "node_id": "string",
  "orchestrator": {
    "connected": true,
    "last_seen": "string",
    "url": "string"
  },
  "pipelines": [
    {
      "id": "string",
      "name": "string",
      "status": "string",
      "version": 0
    }
  ],
  "resources": {
    "cpu_percent": 0,
    "disk_percent": 0,
    "goroutines": 0,
    "memory_percent": 0
  },
  "start_time": "string",
  "status": "healthy",
  "uptime": "string",
  "version": "string"
}