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Building LiveAI™ systems

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

Live Data Framework

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.

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Use cases

Pricing

Pathway Live Data Framework offers flexible plans to suit collections of any size. Learn more.

Spin up your live pipelines in minutes.
Try it out

Pathway's Application templates allow you to quickly put in production AI applications which offer high-accuracy RAG at scale using the most up-to-date knowledge available in your data sources.

Pathway connects to your data sources (file systems, databases, APIs) in real-time, ensuring your AI pipelines always work with the latest information.

Key Benefits:

  • Seamless Data Integration: Connect to a variety of data sources from Enterprise file systems, Kafka, real-time data APIs, to Sharepoint, S3, PostgreSQL, Google Drive, etc.
  • Real-Time Indexing: Keep your data up-to-date for accurate and relevant results. All new data additions, deletions, updates are automatically taken into account.
  • Advanced Search Capabilities: Built-in data indexing enabling vector search, hybrid search, and full-text search - all done in-memory, with cache.
  • No Infrastructure Hassle: Deploy easily with no additional infrastructure setup.

How it works

Pathway Architecture

They Trust us

db-schenker logotype
intel logotype
nato logotype
F1 logotype
la-poste logotype
transdev logotype
cma-cgm logotype
Mazars logotype
CLS logotype
db-schenker logotype
intel logotype
nato logotype
F1 logotype
la-poste logotype
transdev logotype
cma-cgm logotype
Mazars logotype
CLS logotype

Use cases

Pricing

Pathway AI pipelines offer flexible plans to suit collections of any size. Learn more.

Fully customizable in Python
Deploys with Kubernetes
Runs on cloud, runs in a data center, runs in a Faraday cage
Spin up your all-inclusive RAG pipelines in minutes.One containerized service, no infrastructure dependencies. Try it out
  • High accuracy knowledge retrieval
  • Live synchronization with data sources
  • Unstructured document support (PDF, DOC,...)
  • Fast built-in vector indexing up to millions of documents*