Eradicate pipeline bottlenecks
Diagnose, validate & remediate broken pipelines in minutes
Data pipeline problems often eat up hours, if not days, in identifying and solving intricate issues. Linea drastically cuts down this time, ensuring rapid issue detection and resolution, whilst simultaneously making pipelines resilient to future challenges.
Linea dramatically reduces the amount of time debugging, validating and deploying fixes to production pipelines,
all while making them more resilient going forward. Below are some of our core capabilities that make this happen.
Swiftly locate the exact pipeline task where an error occurred, cutting down critical time normally spent on manual searches.
Launch a development environment that exactly mirrors production, ensuring accurate error reproduction.
Automatically create test cases based on problematic inputs, fortifying pipelines against future errors.
Deploy fixes easily, integrating seamlessly with the most common orchestration platforms.
Integrate with your existing data stack including orchestrators and data quality tools.
Maintain a historical record of code versions, to compare changes and understand the evolution of pipeline tasks.
Our origins stem from UC Berkeley's RISELab, where the founders of Databricks came from. Our team has a wealth of industry experience in MLOps from leading AI organizations such as LinkedIn, Google, Scale AI, Domino Data Lab, Microsoft, and NASA. We're proud to have the support of renowned advisors and investors, including the co-founders of Databricks and Kaggle, as well as the former US Chief Data Scientist.
We've been fortunate to receive a significant amount of seed stage funding from top-tier venture funds:
Are you passionate about transforming the world of data engineering? At Linea, we're pioneering innovative solutions to make data pipelines more efficient, resilient, and user-friendly. If you're excited to face challenging problems, collaborate with a dynamic team, and shape the future of data infrastructure, we can't wait to meet you.