Openlayer is a powerful testing and observability platform for ML. It lets you collaborate with others on finding issues in models and data, debugging them, and committing new versions.
Very cool approach to ML testing. I like how you track against commits and help define goals as you define the pipeline. One question - how do define the "root cause" that you mention when solving failed goals?
Great integrated product for giving visibility into ML models, highly recommend for anyone looking for a way to benchmark, evaluate, and iterate on their models (which everyone should!)
This is awesome! Having a great debugging workspace on par with software engineering debugging has always been a pain point to me when working on finance data and autonomous driving. What are some of the use cases you enable today?
Optimizing an ML model at scale requires a bunch of different tools and lots of work by the engineers + data scientists. Love that Openlayer can do all of this for a company (detect errors, suggest new optimizations, etc.), definitely a game-changer for ML teams! 👏🏾
I love OpenLayer because it allows not just engineers, but PMs, analysts, and managers to participate in the ML development process. Finally, a way to catch errors before the product gets into the hands of users!
