We developed AlgoRun initially out of necessity starting as far back as 2015. We set out to empower traditional software development teams to better interface with the data science projects. (and vice versa) Taking a data science project from the lab to production has been and continues to be a difficult problem to solve.

AlgoRun was designed to be ultra-flexible by enabling highly composable and loosely coupled data processing pipelines. Being programming language agnostic and cloud agnostic allows for integration with today’s latest and greatest machine learning tooling yet be ready for what is coming tomorrow.

AlgoRun is built to make getting to production as painless as possible.

We specialize in documenting, organizing, packaging and deploying enterprise data pipelines. We make sense of all the incredible work your data science team produces and prepare it for the real world. We typically work on tasks like enhancing your ETL processes for the cloud and full end-to-end deployment of internet scale machine learning pipelines. We are passionate about helping you productionize all your AI efforts.

AlgoRun is composed of many great open source projects and is intended to be the “glue” that simplifies your AI Orchestration journey.

While there are other similar frameworks out there, none have fulfilled all our requirements:

– Focus on model inference and deployment

– Language agnostic

– Ease of extension

– Flexibility to handle any data processing pipeline

This led us to build AlgoRun to fill in gaps we’ve ran into while also using some of the wonderful existing frameworks out there.

Currently AlgoRun is partially open source. We continue to contribute to the open source projects that are integrated into AlgoRun. Some of the incubating codebases are still being developed internally. Enterprise customers have the ability to access the source code for all core system codebases.

AlgoRun is constantly evolving to help data teams build and deploy their AI products and services. With the rapid pace of change in this space, we are constantly integrating new features that will power the AI infrastructure of the future.

For more details, this is our roadmap.

Have something you’d like built into the platform? Share your feedback!