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Average Ratings 0 Ratings
Description
Flyte is a robust platform designed for automating intricate, mission-critical data and machine learning workflows at scale. It simplifies the creation of concurrent, scalable, and maintainable workflows, making it an essential tool for data processing and machine learning applications. Companies like Lyft, Spotify, and Freenome have adopted Flyte for their production needs. At Lyft, Flyte has been a cornerstone for model training and data processes for more than four years, establishing itself as the go-to platform for various teams including pricing, locations, ETA, mapping, and autonomous vehicles. Notably, Flyte oversees more than 10,000 unique workflows at Lyft alone, culminating in over 1,000,000 executions each month, along with 20 million tasks and 40 million container instances. Its reliability has been proven in high-demand environments such as those at Lyft and Spotify, among others. As an entirely open-source initiative licensed under Apache 2.0 and backed by the Linux Foundation, it is governed by a committee representing multiple industries. Although YAML configurations can introduce complexity and potential errors in machine learning and data workflows, Flyte aims to alleviate these challenges effectively. This makes Flyte not only a powerful tool but also a user-friendly option for teams looking to streamline their data operations.
Description
KINEXON collects real-time localization information and converts it into impactful actions for various sectors, including industry, sports, and entertainment. Unlock insights that were previously out of reach by utilizing our advanced technology, allowing you to turn data into strategic advantages. Are you aware that you can enhance operational efficiency by harnessing real-time location data from interconnected assets for applications like automated order processing, quality assurance, or inventory restocking? By automating processes that involve numerous moving assets, you can greatly reduce the risk of human error and the burden of time-consuming manual operations, leading to heightened overall efficiency. With millions of containers utilized globally in manufacturing, poor management of these assets can lead to significant waste of both time and financial resources. Implementing automated container management systems, which rely on accurate RTLS data regarding container locations and status on the production floor, significantly boosts transparency and utilization of containers, ultimately optimizing operations. Moreover, this level of efficiency can lead to a more streamlined workflow and improved productivity across the board.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Apache Hive
Yes
Apache Parquet
Yes
Dask
Yes
Databricks
Yes
Dolt
Yes
Feast
Yes
Google Cloud BigQuery
Yes
Great Expectations
Yes
Kubernetes
Yes
Integrations
Amazon SageMaker
No
Apache Hive
No
Apache Parquet
No
Dask
No
Databricks
No
Dolt
No
Feast
No
Google Cloud BigQuery
No
Great Expectations
No
Kubernetes
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Union.ai
Founded
2020
Country
United States
Website
flyte.org
Vendor Details
Company Name
KINEXON
Founded
2012
Country
Germany
Website
kinexon.com
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
IoT
Application Development
No
Big Data Analytics
No
Configuration Management
No
Connectivity Management
No
Data Collection
No
Data Management
No
Device Management
No
Performance Management
No
Prototyping
No
Visualization
No