ForestFlow 

[wtm_mlop_cats] ForestFlow is a scalable policy-based cloud-native machine learning model server. ForestFlow strives to strike a balance between the flexibility it offers data scientists and the adoption of standards while reducing friction between Data Science, Engineering and Operations teams. ForestFlow is policy-based because we believe automation for Machine Learning/Deep Learning operations is critical to scaling […]

Fiddler

[wtm_mlop_cats] Progress® Telerik® Fiddler Everywhere is a web-debugging tool that monitors, inspects, edits, and logs all HTTP(S) traffic, and issue requests between your computer and the Internet, and fiddles with incoming and outgoing data. It is a high performance, cross-platform proxy for any browser, system, or platform. Features Fiddler Everywhere delivers a range of handy […]

Evidently 

[wtm_mlop_cats] Evidently helps evaluate and monitor machine learning models in production. It generates interactive reports or JSON profiles from pandas DataFramesor csv files. You can use visual reports for ad hoc analysis, debugging and team sharing, and JSON profiles to integrate Evidently in prediction pipelines or with other visualization tools. Features The primary use for […]

DeepDetect  

[wtm_mlop_cats] DeepDetect is a deep learning API and server written in C++11, along with a pure Web Platform for training and managing models. DeepDetect aims at making the state of the art deep learning easy to work with and integrate into existing applications. It has support for backend machine learning libraries Caffe, Caffe2, Tensorflow, XGBoost, […]

Cortex 

[wtm_mlop_cats] Cortex’s AI analyzes all the content from: Your BrandCompetitorsYour IndustryInfluencersMedia OutletsMuch MoreThen shows you all the creative choices that are paying off – and those that aren’t. Features Serverless workloadsRealtimeRespond to requests in real-time and autoscale based on in-flight request volumes.AsyncProcess requests asynchronously and autoscale based on request queue length.BatchRun distributed and fault-tolerant batch […]

BudgetML

[wtm_mlop_cats] BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it’s hard to find a simple way to get a model in production fast and […]

BentoML

[wtm_mlop_cats] BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multiple ML frameworks, including Tensorflow, PyTorch, Keras, XGBoost and moreCloud native deployment with Docker, Kubernetes, AWS, Azure and many moreHigh-Performance online API serving and offline batch servingWeb dashboards and APIs for model registry and deployment management Features Production-ready online […]

Backprop  

[wtm_mlop_cats] Backprop is a serverless model platform that makes it simple for developers to use machine learning models in any application. Using models is done via Tasks, such as Question answering and Image classification. Tasks act as a middleman between a request and a model, which makes it easy to use a variety of models […]