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
Call LLM and embedding models as pipeline steps, locally or via cloud providers
Built-In Governance
Mask PII and enforce policies before data leaves the edge
Platform Agnostic
Works with Kafka, Snowflake, S3, and more
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.
- AI in Your Pipelines: Call LLM and embedding models as native pipeline steps, locally via Ollama or through OpenAI, AWS Bedrock, and Vertex AI.
- 200+ Components: Pre-built inputs, processors, and outputs for any pipeline need.
- Visual Pipeline Builder: Build pipelines visually, or author them in YAML.
- 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:
- Sign up for Expanso Cloud (free tier available)
- Install an agent on your infrastructure
- Build a pipeline using our visual builder or YAML
Popular Use Cases
- Database Connectivity: Connect to MySQL, PostgreSQL, SQLite for edge analytics and caching.
- Edge Infrastructure Management: Manage K3s clusters, Docker containers, collect logs, automate operations.
- Log Processing: Filter debug logs, mask PII, route to multiple destinations.
- IoT Data Aggregation: Aggregate sensor data at the edge, reducing volume by 90%.
- Real-Time Alerting: Detect patterns and alert without backend latency.
- Compliance & Privacy: Mask sensitive data before it leaves your network.
Core Features
Visual Pipeline Builder
Create sophisticated pipelines visually or in YAML. Preview data transformations in real time as you build.
Edge AI & ML
Call large language and embedding models directly on streaming data as a native pipeline step, locally with Ollama or through providers like OpenAI, AWS Bedrock, and Google Vertex AI.
- Local or Cloud Inference: Run models locally with Ollama, or call managed provider APIs.
- Enrich Data: Add model outputs (like a classification or 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 drops noisy logs and masks PII at the edge before archiving the rest to S3:
input:
kafka:
addresses: [kafka:9092]
topics: [app-logs]
pipeline:
processors:
- mapping: |
# Parse each log line and drop noisy debug logs at the edge
root = this.parse_json()
root = if root.level == "debug" { deleted() }
- mapping: |
# Mask PII on the logs that remain
root = this
root.user.email = this.user.email.hash("sha256")
root.user.ip = deleted()
output:
aws_s3:
bucket: log-archive
path: "${! timestamp_unix() }-${! uuid_v4() }.json"
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.
- Quick Start Guide - Your first pipeline in 15 minutes
- Core Concepts - Understand how Expanso works
- Installation - Deploy agents on your infrastructure
🔧 How-To Guides - Solve Specific Problems
Already familiar with the basics? Find step-by-step solutions to common problems.
Most Popular:
- How to Remove PII from Data Streams
- How to Send Data to Multiple Destinations
- How to Enforce Data Schema Validation
📋 Component Reference - Browse Available Components
Need to look up a specific input, processor, or output? Browse our complete component catalog.
- 200+ Components - Complete catalog with configuration options
Quick Links by Task
I want to...
- Deploy my first pipeline → Quick Start Guide
- Remove sensitive data → Remove PII Guide
- Send data to multiple systems → Fan-Out Pattern Guide
- Validate data quality → Schema Enforcement Guide
- Browse available components → Component Catalog
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 can call large language and embedding models as native pipeline steps. Run them locally with Ollama, or use managed providers like OpenAI, AWS Bedrock, and Google Vertex AI. Enrich events with model outputs (like classifications or risk scores) and route on the results.
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, Kafka, SQL databases). Browse the complete catalog in our Component Reference.
Do I need to write code to build pipelines?
No, use our 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
- Email Support: [email protected]
- Community: Join our Slack
Ready to get started? Jump to the Quick Start guide →