Unify Your AI Development On A Single, End-to-End Platform

“By using Flyte, Stash cut its provision time by 50%, reduced its model execution time by 65% and lowered its compute costs by 67%. “What’s great now is that every single new model that comes out is being done on Flyte, and it's really exciting to be working with the modelers and having them write their own workflows… They’re becoming more and more self-sufficient with every single release.”

“From several pipelines we migrated to Flyte from our legacy tools, we see around 20% to 80% cost saving. Optimistically, we will have around 100-200 new workflows added to Flyte per month”

“Without Flyte Agents, we would need to refactor our legacy models by recreating them, evaluating performance, productionizing, etc. This is not trivial, and no business wants to take on this type of effort, especially if the model is not broken. We were able to save nine months of engineering time by avoiding any code changes, and simply lifting and shifting our Airflow code and running it with Union.”

“Based on a single team we’ve seen 10x more training jobs dispatched from Flyte, resulting in 5x more frequent model releases with sizable business gain… the realization here is that ML productivity is not a nice to have, it is a busin

“From locally trained models to remote, reproducible training pipelines. One of the main benefits from using Flyte is that the data scientists don’t need to understand Kubernetes… they can concentrate on what they do best.”

“Flyte has been the workhorse of our system, producing actionable concentration and flux data since the very beginning. Flyte's SDK allows us to quickly integrate our algorithms and its control plan has let us scale to 10k nodes without issue. We look forward to moving over to Union.ai's managed offering as we move into full operations, freeing us up to drive even MORE impact and shape policy with MethaneSAT data.”

“Union is a key accelerant for us at Physical Intelligence. We needed a centralized platform that would allow us to run our ML data processing workflows at scale without worrying about the infrastructure. Union delivered exactly that. The platform's plugin ecosystem also allowed us to quickly integrate the libraries & tools we were already using, saving us a lot of time and effort. We ramped up and had key production workloads running quickly. Without Union, we wouldn't have gotten into production this quickly.”

“Flyte has been a game changer for us. Flyte enabled rapid development and iteration cycles, reducing time-to-start for experiments from 10-15 minutes to under a minute on average. We were able to take control of and lower our compute costs despite a growing number of projects.”

“Union AI allows us to manage complex workflows that process hundreds of terabytes of data across more than 10,000 machines with efficiency and reliability.”

“Flyte has been instrumental in accelerating our ETL and model training pipelines, for swift iteration, streamlined dev process, and quicker time-to-market.”

“Flyte enabled us to run millions of jobs for our neural simulator that we migrated from Databricks.”

“Flyte has been the workhorse of our system, producing actionable concentration and flux data since the very beginning. Flyte's SDK allows us to quickly integrate our algorithms and its control plan has let us scale to 10k nodes without issue. We look forward to moving over to Union.ai's managed offering as we move into full operations, freeing us up to drive even MORE impact and shape policy with MethaneSAT data.”

“We often have a very fast-cycle exploratory collaboration in sort of a computational notebook context between a scientist and a data scientist to begin framing an amorphous scientific problem down into some kind of computational tool or solution. Then we have another handoff in collaboration between a data scientist and an engineer to really take that prototype system and knit that into our production infrastructure. We collaborate across that entire stack, and we need a tool set that supports that.”

“Without Flyte, we couldn’t have done what we’ve done so far with the people that we have. You need a workflow orchestration engine if you’re going to do ML at our level, and Flyte is the best one.”

“With Union, we can co-locate pod specifications and compute resource requirements directly with our tasks and workflows. It reduces at least by 2x the time it takes to make changes to the compute resources for our workflows.”

“There’s actually less than a handful of [Kubernetes-native workflow engines], and Flyte was one of them,” Balakrishnan says. “But what was also important to us was that it needed to have a sense of credibility and to be battle-tested. “It’s not an understatement to say that Flyte is really a workhorse at Freenome!”

“[Flyte is] the de facto workflow orchestration engine. I really think Flyte has got the model correct, absolutely correct with respect to architecting and deploying workflows as both code first and leveraging the Kubernetes scheduler to abstract away the scheduling on a per-task granularity.”

”Union is a key accelerant for us at Physical Intelligence. We needed a centralized platform that would allow us to run our ML data processing workflows at scale without worrying about the infrastructure. Union delivered exactly that. The platform's plugin ecosystem also allowed us to quickly integrate the libraries & tools we were already using, saving us a lot of time and effort. We ramped up and had key production workloads running quickly. Without Union, we wouldn't have gotten into production this quickly.“

“Flyte has been a game changer for us. Flyte enabled rapid development and iteration cycles, reducing time-to-start for experiments from 10-15 minutes to under a minute on average. We were able to take control of and lower our compute costs despite a growing number of projects.”

“Flyte enabled us to run millions of jobs for our neural simulator that we migrated from Databricks.”

“Union AI allows us to manage complex workflows that process hundreds of terabytes of data across more than 10,000 machines with efficiency and reliability.”

“Flyte is an ideal blend of out-of-the-box features and adaptability while leveraging modern technologies to successfully delivered significant business value.”

“Flyte’s scalability, data lineage, and caching capabilities enable us to train hundreds of models on petabytes of geospatial data which gives us an edge in our domain.”