MLOps Features
at Your Fingertips
at Your Fingertips
ENFINT MLOps Platform helps business offering full lifecycle
of DS/ML projects development and operations
MLOps Features
at Your Fingertips
ENFINT MLOps Platform helps business offering full lifecycle of DS/ML projects development and operations
Start to manage your Data Science/Machine Learning projects right from day one
One Platform to Run Corporate MLOps
Start to manage your Data Science/Machine Learning projects right from day one
Notebooks
To cover model development, training and verification, ENFINT MLOps Platform provides managed development environments based on Jupyter, Visual Studio Code and RStudio.
MLflow
To track experiments and register models, integrated MLflow component is ready.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
Airflow
To orchestrate batch jobs Apache Airflow along with Git integration is used.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
Seldon Core
To run models as online services, Seldon Core component provides quick deployment pipelines.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Feature Store
To discover, manage and serve your data, ENFINT MLOps Platform has built-in feature store component based on Feast and its API. It allows users to classify and manage data properly within historical storages and online databases.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Model Monitoring
To cover monitoring part of the lifecycle, ENFINT MLOps Platform provides a set of monitoring capabilities based on Evidently, Grafana, Prometheus and Jaeger.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
Notebooks
To cover model development, training and verification, ENFINT MLOps Platform provides managed development environments based on Jupyter, Visual Studio Code and RStudio.
MLflow
To track experiments and register models, integrated MLflow component is ready.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
Airflow
To orchestrate batch jobs Apache Airflow along with Git integration is used.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
Seldon Core
To run models as online services, Seldon Core component provides quick deployment pipelines.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Feature Store
To discover, manage and serve your data, ENFINT MLOps Platform has built-in feature store component based on Feast and its API. It allows users to classify and manage data properly within historical storages and online databases.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Model Monitoring
To cover monitoring part of the lifecycle, ENFINT MLOps Platform provides a set of monitoring capabilities based on Evidently, Grafana, Prometheus and Jaeger.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
Project work becomes easier thanks to an intuitive workflow and built-in DS/ML tools
Projects
Configure projects to solve your business challenges.
All requirements, data sources, notebooks and models are conveniently managed within one project and secured with proper segregation of duties and access control lists.
All requirements, data sources, notebooks and models are conveniently managed within one project and secured with proper segregation of duties and access control lists.
Workspaces
Configure notebooks for your team based on their needs and project requirements.
Platform supports popular programming languages and IDEs.
Along with predefined images users can also create new images based on their preferences and previous experience.
Platform supports popular programming languages and IDEs.
Along with predefined images users can also create new images based on their preferences and previous experience.
Proven Open Source Components
Develop with Jupyter, VSCode and RStudio.
Track experiments and register models with MLflow.
Analyze and engineer data with our Feature Store. Deploy batch models with Airflow or transform models into services via Seldon Core.
Track experiments and register models with MLflow.
Analyze and engineer data with our Feature Store. Deploy batch models with Airflow or transform models into services via Seldon Core.
Monitoring
Track and maintain production models in real time.
Configure dashboards using set of available monitors and triggers. Receive alerts and react rapidly.
Configure dashboards using set of available monitors and triggers. Receive alerts and react rapidly.
Project work becomes easier thanks to an intuitive workflow and built-in DS/ML tools
Projects
Configure projects to solve your business challenges.
All requirements, data sources, notebooks and models are conveniently managed within one project and secured with proper segregation of duties and access control lists.
All requirements, data sources, notebooks and models are conveniently managed within one project and secured with proper segregation of duties and access control lists.
Workspaces
Configure notebooks for your team based on their needs and project requirements.
Platform supports popular programming languages and IDEs. Along with predefined images users can also create new images based on their preferences and previous experience.
Platform supports popular programming languages and IDEs. Along with predefined images users can also create new images based on their preferences and previous experience.
Proven Open Source components
Develop with Jupyter, VSCode and RStudio.
Track experiments and register models with MLflow. Analyze and engineer data with our Feature Store. Deploy batch models with Airflow or transform models into services via Seldon Core.
Track experiments and register models with MLflow. Analyze and engineer data with our Feature Store. Deploy batch models with Airflow or transform models into services via Seldon Core.
Monitoring
Track and maintain production models in real time.
Configure dashboards using set of available monitors and triggers. Receive alerts and react rapidly.
Configure dashboards using set of available monitors and triggers. Receive alerts and react rapidly.
Level up your team work with ENFINT MLOps Platform
Embedded Open Source components
MLflow, Airflow, Jupyter and other DS/ML instruments are provided out-of-the-box
Python, R, Java and Scala support
Ability to work in IDE images with support of proven machine learning tools
Customization through
code
code
Wide platform customization capabilities are available
Authentication and authorization
Single and secured web interface for platform components
Resource management
Accurate resource limits and quotas control for project nodes
Scalability and fault-tolerance
Platform meets customer high standards for scalability and fault-tolerance
Level up your team work with ENFINT MLOps Platform
Embedded open-source components
MLflow, Airflow, Jupyter and other DS/ML instruments are provided out-of-the-box
Python, R, Java and Scala support
Ability to work in IDE images with support of proven machine learning tools
Customization through
code
code
Wide platform customization capabilities are available
Authentication and authorization
Single and secured web interface for platform components
Resource management
Accurate resource limits and quotas control for project nodes
Scalability and fault-tolerance
Platform meets customer high standards for scalability and fault-tolerance
Major changes in your business processes
Speed up decision-making and shorten time-to-market with ENFINT MLOps Platform
- React instantly and accurately with quick deployment of your models
- Control every step of your ML project with mature projects lifecycle
- Reduce development and production efforts with efficient tools and frameworks
Excellent teamwork under one roof
Efficient
Use only known and proven DS\ML tools, integrated into the platform for quick development and implementation
Manageable
Assign roles to your team members, set up deadlines for key project milestones and approve major operations
Transparent
Configure alerts and receive
immediate notifications for important
project activities
immediate notifications for important
project activities
Excellent teamwork under one roof
Efficient
Use only known and proven DS\ML tools, integrated into the platform for quick development and implementation
Manageable
Assign roles to your team members, set up deadlines for key project milestones and approve major operations
Transparent
Configure alerts and receive
immediate notifications for important
project activities
immediate notifications for important
project activities
ENFINT MLOps Platform supports diverse projects for different industries
ENFINT MLOps Platform supports diverse projects for different industries
Finance & Banking
Credit rating, fraud detection models, real-time offerings generation
Manufacturing
Operations efficiency, supply chain analysis and predict, service delay prevention models
Marketing & Retail
Income growth and loyalty program models, consumer behavior and product bundles analysis, staff strategy management
Finance & Banking
Credit rating, fraud detection models, real-time offerings generation
Manufacturing
Operations efficiency, supply chain analysis and predict, service delay prevention models
Marketing & Retail
Income growth and loyalty program models, consumer behavior and product bundles analysis, staff strategy management
Deployment options
Select one that meets your corporate policy
In-house deployment within your
enterprise infrastructure
Public cloud
infrastructure deployment
Deployment options
Select one that meets your
corporate policy
corporate policy
In-house deployment within your enterprise infrastructure
Public cloud infrastructure deployment
Case Studies
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