Building live AI systems

Underpinned by the fastest data processing engine on the market, Pathway's offering includes infrastructure components that fuel live AI systems from dynamic sources of structured and unstructured data, enabling decision-making based on always up-to-date knowledge

Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

Key Benefits:

Easy Integration: Easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries
Flexible Deployment: Use it in both development and production environments
Real-time Processing: Handle both batch and streaming data efficiently. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams
High Performance: Powered by a scalable Rust engine for optimized performance, enabling multithreading, multiprocessing, and distributed computations
Simplified Deployment: Deploy easily with Docker and Kubernetes

How it works

Streamlined Cloud-Native Development Built in Rust with ❤ for Python developers, Pathway streamlines the entire ML/AI project lifecycle from prototype to production. It supports local, notebook, and scaled container deployments.

Fast, and Always In-Sync. Connect live data sources like SharePoint, Google Drive, S3 and Delta Tables, cloud folders, Kafka, databases, and 300+ APIs such as Salesforce and Hubspot. Pathway's high-speed Rust engine delivers real-time updates, and is scalable to hundreds of CPU cores, with cost-efficient incremental computing, persistence, and caching.

A single robust container. You own it. Deploy each of your Pathway applications from a git folder using Docker or Kubernetes, on-premises or in any cloud. Simplify your setup by avoiding multiple databases and compute engines linked by clunky APIs. Gain full control of the pathway that your data follows. It is made available for download as a Python-native package from GitHub

Chef's Choice, or à la carte? Have it your own way. Choose from ready-to-use Pathway app templates suitable for various industries and data types. Customize them using functions from the Pathway library, connectors, and integrations. Safely interact with LLMs and external asynchronous APIs.