Event-driven Data Pipelines for AI Startups
Focus on writing your data transformations—we'll handle the infrastructure. Build scalable RAG pipelines without the complexity of Apache Kafka or Flink.
import json
import requests
def handler(data, log):
key = os.getenv("GEOAPI_KEY")
enriched_location = enrich_location(data)
data.update({
"latitude": enriched_location["lat"],
"longitude": enriched_location["lon"],
"postcode": enriched_location["postcode"],
})
return data
Native Python
Real-time Processing
Trusted by developers worldwide
A selection of use cases
Each feature is built to make your event-driven data pipeline journey as easy as possible and allow any Py dev to create pipelines in minutes.
Use Case: PII masking
Automatically detect and mask sensitive information in real-time data streams using advanced AI models.
Use Case: Spam detection
Implement real-time spam detection using machine learning models and custom filtering rules.
Use Case: Data enrichment
Enhance your data streams with additional context and information from external sources.
Built with robust technologies
Native Python support
Real-time processing
Scalable infrastructure
Features
Each feature is built to make your event-driven data pipeline journey as easy as possible and allow any Py dev to create pipelines in minutes.
Fully managed and serverless
You write the functions and we run the infra. Independently create, deploy, and manage data pipelines.
Auto-mode pipeline creation
Trigger pipelines creations in auto mode with Python. No more manually creating pipelines for new customers.
BYOC Enterprise Support
BYOC for you and your enterprise customers. We take care of the maintenance and updates.
Create your first pipeline in minutes
Our low code interface shows you with a step-by-step guide how create your first pipeline.
Works with your preferred data stack
Less Infrastructure. More Outcome.
Build scalable RAG pipelines without the complexity
Zero Infrastructure
You define the pipeline logic and we execute it. Simple.
Native Python
End-to-end native Python for your pipelines. Forget the Python wrappers and use any Py library you want.
Build in mins
Set up your pipeline in just minutes. Get auto scaling of your infra, low latency and optimal data retention.
Supported by our users
Do not listen to us. Listen to them.
"GlassFlow team managed to turn my scattered thoughts regarding the data streaming into a Python masterpiece."
Anurag Roy
@Doorlabs
"Creating a data pipeline with GlassFlow is incredibly straightforward"
Swapnil Gupta
@Deloitte
"I am fed up with overcomplicated event-based pipelines. Finally a team that will make my life easier."
Philippe Brule
@aboutphilippe
Works with your preferred data stack
Integrate with your data sources and destinations that you are already using. Our Py SDK and our managed connectors make is easy for you.
OpenAI
Seamlessly integrate with OpenAI's powerful AI models for advanced data processing
AWS Kinesis
Direct integration with AWS Kinesis for real-time data streaming capabilities
Google Pub/Sub
Connect directly with Google Cloud's messaging and streaming data service
Advanced Integration Support
Our platform supports a wide range of data sources and destinations, making it easy to build complex data pipelines with minimal setup.
Connect with leading platforms
Integrate with OpenAI, AWS, Google Cloud, and more. Our platform supports your entire data stack.
