Request a demo
Join a short walkthrough of Xorq. We'll explain how to build, run, serve, and govern your AI data processing with Xorq.
"The Xorq framework greatly simplified our ML pipelines, improving performance 10x and reducing the compute and storage resources required to run them."
What we'll cover
Live syntax demo
See how Xorq processes any type or amount of data from across multiple data sources—with a focus on your specific use cases.
Deployment options
From local dev to production on any platform. We'll share composability and reuse best practices as well as scaling and security.
Lineage & governance
We'll explain Xorq lineage and observability features that help you maintain quality and productivity as your team and AI infrastructure grow.
Just build, run, and serve.
Declare and compile multi-engine Python
Xorq catalogs every expression: versioned, composable, lineage-tracked artifacts represented as YAML format.
Build Once, Run Anywhere.
Run Xorq expressions as portable UDXFs with cross-engine optimizations, caching & observability.
High-performance Catalog Servers
Create portable Catalog Servers, with millisecond data transfer via Apache Arrow Flight.
Who you'll meet
Meet the passionate pros who’ll introduce you to Xorq and how it can help accelerate your data science and AI data engineering.
Passionate about creating innovative solutions that accelerate enterprise AI. Previously, held leadership roles at Voltron Data, Capital One, and Amazon. Co-founder of PyData DC.
A software engineer based in Barcelona, with experience working on data science, machine learning, and microservices architectures. An active contributor to open source projects such as Dask, Xarray, Geopandas, Ibis, and Apache DataFusion.
A data scientist and software engineer with over a decade of experience in quantitative infrastructure at MIT Probabilistic Lab, Two Sigma, and others before co-founding Xorq with Hussain.
"The Xorq framework greatly simplified our ML pipelines, improving performance 10x and reducing the compute and storage resources required to run them."
Simplify your ML stack
Request a walkthrough and see how Xorq redefines what a pipeline can be.
