Sold by: Deeploy
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Deeploy Core includes the core functionality of our Responsible AI Platform that enables companies to stay in control of their ML models. Easily bring truly responsible models into production, without compromising on your governance requirements, even for high-risk use cases.
Overview
Nowadays, transparency, explainability and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility.
Easily integrate Deeploy Core with your existing AWS stack. Deploying and maintaining ML systems requires involvement of people and tools. Deeploy Responsible AI software giving data science teams autonomy to create and maintain their models.
The challenges Deeploy solves:
- A safe and responsible MLOps environment: organized and monitored deployments
- Explain and understand AI decisions: create human-AI interaction with experts
- Traceback how decisions are made: be able to correct, report and reproduce.
Highlights
- A safe and responsible MLOps environment: organized and monitored deployments
- Explain and understand AI decisions: create human-AI interaction with experts
- Traceback how decisions are made: be able to correct, report and reproduce
Details
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Delivery method
Delivery option
Main installation
Default
Latest version
Operating system
Linux
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 14 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/unit/hour |
|---|---|---|
Hours | Container Hours | $0.07 |
Vendor refund policy
Deeploy Core is not eligible for refunds, but customers are free to cancel anytime.
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Main installation
Supported services: Learn more
- Amazon EKS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
New features
-
Custom monitoring metrics Visualize your own metrics in the new Custom tab in Deployment monitoring. Add up to four custom metrics; calculate the data points you want to visualize and upload them using the Deeploy python client or API.
-
Flexible input and output schema mapping Leverage Deeploy's full monitoring capabilities for external and custom Docker models with request and response mapping. Define a JSON mapping in your metadata for models that do not adhere to Deeploy's standard.
Improvements
- Created a new navbar and Workspace selector to easily navigate between Workspaces
- Improved error handling for connecting to an external object storage
- Detached the selection of nodes from selecting custom resources (Private cloud only)
- Improved validation for the validUntil property of tokens and personal key pairs
- Added state for missing metadata in the Deployment details
- Stricter validation on environment variable keys to prevent confusing Deployment errors
- Improved error handling for failed Deployment updates
Bug fixes
- Fixed an issue with upgrading Deployments to external or managed
- Fixed an issue where Deployments with a large amount of prediction logs couldn't be deleted
Additional details
Usage instructions
The general installation steps are as follows: a. Make sure to follow the installation steps as described here: https://docs.deeploy.ml/installation/amazon-eks/eks-2 b. Install the Deeploy software requirements and helm chart. For the latest stable release checkout: https://artifacthub.io/packages/helm/deeploy-core/deeploy . Use the Deeploy helm chart repository and follow the instructions in the README: https://gitlab.com/deeploy-ml/deeploy-install .
Resources
Vendor resources
Support
Vendor support
Default community support is included. Additional support and SLA are available on request: sales@deeploy.ml .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Deeploy Core - Monthly
By Deeploy
Deeploy Core includes the core functionality of our Responsible AI Platform that enables companies to stay in control of their ML models. Easily bring truly responsible models into production, without compromising on your governance requirements, even for high-risk use cases.
Customer reviews
Information Technology and Services
Simplified deployment and monitoring of ML models
Reviewed on Nov 24, 2023
Review provided by G2
What do you like best about the product?
Ease of use and intuitive flow allows team members with limited engineering knowledge to deploy and then monitor ML models in production.
What do you dislike about the product?
Error messaging has been quite uninformative in some cases, but I have to admit that this has improved in recent updates.
What problems is the product solving and how is that benefiting you?
Deeploy speeds up deployment and monitoring of models, especially in a data team with limited capacity (FTE) and engineering knowledge.
Leave a comment0 comments
Computer Software
Useful and responsible tool
Reviewed on Nov 16, 2023
Review provided by G2
What do you like best about the product?
Deeploy has increased productivity as my data science team can now deploy all models in the same place, which allows us to better manage models and monitor their performance. But what really sets it apart is the possibilities it brings for explainability and the use of human feedback.
What do you dislike about the product?
The documentation was still a bit limited
What problems is the product solving and how is that benefiting you?
Ease od deploying and explainability feature that was out-of-the-box
Computer Software
Combining MLOps, explainability and AI governance
Reviewed on Sep 18, 2023
Review provided by G2
What do you like best about the product?
The ease to deploy an AI model, with out-of-the-box explainability and the necessary governance & compliance tools and monitoring functionalities. It also runs smoothly on both Azure and AWS, when working with our customers.
What do you dislike about the product?
We're waiting on a few more integrations.
What problems is the product solving and how is that benefiting you?
Stay in control (governance / compliance)
Provide transparency
Provide trust to end users
Model deployment & updates
Monitoring
Provide transparency
Provide trust to end users
Model deployment & updates
Monitoring