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Expanso Documentation

Expanso enables you to deploy and orchestrate data pipelines from edge to destination through a unified control plane. Process, filter, and transform data - and run AI models - before it hits your backend platforms.

Deploy intelligent data pipelines anywhere

Process data and run inference where it's generated. Cut costs by filtering at the source. Deploy in minutes with 200+ pre-built components.

Cost Reduction

Filter and sample at source - only send valuable data downstream

Edge AI & ML

Run inference models directly within your data pipelines

Built-In Governance

Mask PII and enforce policies before data leaves the edge

Platform Agnostic

Works with Snowflake, Datadog, Splunk, S3 - whatever you use

Start Free Trial Quick Start Guide →

What is Expanso?​

Expanso is a managed platform for deploying intelligent data pipelines at the edge:

  • Edge-Native Architecture: Process data where it's generated - reduce bandwidth and latency.
  • Run AI/ML Models at the Source: Run AI/ML models directly in your data pipelines.
  • 200+ Components: Pre-built inputs, processors, and outputs for any pipeline need.
  • Visual Pipeline Builder: Drag-and-drop interface (YAML also available).
  • Managed SaaS: Central control plane with automatic agent updates.
  • Enterprise Governance: PII masking, policy enforcement, and compliance audit trails.

Quick Start​

Get your first pipeline running in 15 minutes:

  1. Sign up for Expanso Cloud (free tier available)
  2. Install an agent on your infrastructure
  3. Build a pipeline using our visual builder or YAML

Core Features​

Visual Pipeline Builder​

Create sophisticated pipelines with drag-and-drop or YAML. Preview data transformations in real-time as you build.

Edge AI & ML​

Execute machine learning models directly on streaming data as a native pipeline step.

  • Low-Latency Inference: Get predictions in milliseconds without a round-trip to the cloud.
  • Enrich Data: Add model outputs (like a risk score) to your events before routing.
  • Flexible Integration: Integrate with your existing ML workflows and model formats.

Powerful Transformations​

Leverage 200+ built-in components for ingesting, transforming, and routing data:

  • Parse logs (JSON, syslog, CSV, regex)
  • Filter and sample to reduce volume
  • Mask PII automatically
  • Aggregate metrics in time windows
  • Enrich with lookups, APIs, or ML models
  • Route to multiple destinations

Enterprise Ready​

  • Governance: PII detection, masking, and policy enforcement
  • Monitoring: Built-in metrics and health checks
  • Security: RBAC, SSO, audit trails
  • High Availability: Automatic failover and recovery

Example Pipeline​

Here's a pipeline that processes application logs, masks sensitive data, and routes them to multiple destinations:

input:
  kafka:
    brokers: [kafka-broker:9092]
    topics: [transactions]

pipeline:
  processors:
    - mapping: |
        # Parse JSON logs
        root = this.parse_json()

    - model:
        onnx:
          model_path: /models/fraud_detector.onnx
          input_columns: ["transaction_amount", "user_location_risk"]
          output_columns: ["is_fraud_probability"]

    - mapping: |
        # Add risk score to the event
        root.fraud_score = this.is_fraud_probability

        # Mask sensitive user info
        root.user.email = this.user.email.redact_emails()
        root.user.ip = "REDACTED"

output:
  broker:
    pattern: fan_out
    outputs:
      # Send high-risk events to a security queue
      - switch:
          - check: this.fraud_score > 0.9
            output:
              kafka:
                brokers: [kafka-broker:9092]
                topic: high-risk-transactions

      # Send everything to S3 for archiving
      - aws_s3:
          bucket: transactions-archive
          path: "${! timestamp_unix() }-${! uuid_v4() }.json"

See more examples →

Documentation Guide​

We've organized our documentation to help you at different stages of your journey:

🎓 Getting Started - Learn the Basics​

New to Expanso? Start here! These hands-on tutorials will get you up and running quickly.

🔧 How-To Guides - Solve Specific Problems​

Already familiar with the basics? Find step-by-step solutions to common problems.

Most Popular:

📋 Component Reference - Browse Available Components​

Need to look up a specific input, processor, or output? Browse our complete component catalog.

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Frequently Asked Questions​

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.

Community & Support​

Ready to get started? Jump to the Quick Start guide →