Overview

Product video
As organizations scale their AI efforts, governance, transparency, and accountability become essential. Deeploy provides the foundation to deploy and manage AI responsibly, offering the visibility, control, and assurance needed to keep systems reliable and compliant. The platform integrates seamlessly with your AWS environment, unifying data science, engineering, and compliance teams around a single source of truth for AI operations.
Onboard any AI and manage them under one roof: Deeploy centralizes all your AI systems: internal and external AI Systems, ML models, LLMs or AI Agents, regardless of where they run or how they are built. Enabling full oversight without forcing migrations or workflow changes.
Establish robust AI governance: Deeploy enforces consistent validation, documentation, and oversight across all AI systems. Governance standards become embedded in daily workflows, ensuring responsible development and deployment without slowing innovation.
Catch issues before they become liabilities: With real-time monitoring, performance tracking, drift detection, and instant explanations for every prediction, Deeploy ensures AI systems behave as expected. Live dashboards and alerts help teams identify issues early and prevent user impact as data, context, or model behavior shifts.
Close the loop between people and AI: Deeploy enables experts to review and correct AI outcomes, capturing their feedback and highlighting cases where human and AI judgments diverge. This continuous feedback loop improves reliability and strengthens alignment between AI behavior and real-world expertise.
Ensure transparency and traceability: Every model version, data flow, and decision is fully traceable and explainable. Deeploy offers clear auditability and reproducibility, making it easier to maintain trust and meet reporting requirements across teams and stakeholders.
By combining explainability, monitoring, and structured oversight, Deeploy helps organizations stay compliant with evolving regulations such as the EU AI Act or ISO42001. The platform provides the clarity and control needed to operate AI safely and with confidence.
Highlights
- Onboard any AI and manage them under one roof: Deeploy centralizes all your AI systems: internal and external AI Systems, ML models, LLMs or AI Agents, regardless of where they run or how they are built. Enabling full oversight without forcing migrations or workflow changes.
- Establish robust AI governance: Deeploy enforces consistent validation, documentation, and oversight across all AI systems. Governance standards become embedded in daily workflows, ensuring responsible development and deployment without slowing innovation.
- Ensure transparency and traceability: Every model version, data flow, and decision is fully traceable and explainable. Deeploy offers clear audibility and reproducibility, making it easier to maintain trust and meet reporting requirements across teams and stakeholders.
Details
Unlock automation with AI agent solutions

Features and programs
Financing for AWS Marketplace purchases
Pricing
Free trial
Dimension | Description | Cost/unit/hour |
|---|---|---|
Hours | Container Hours | $0.10 |
Vendor refund policy
Deeploy Core is not eligible for refunds, but customers are free to cancel anytime.
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Delivery details
Main installation
- 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
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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.
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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
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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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