Sold by: IBM SoftwareÂ
Deployed on AWS
IBM watsonx.governance as a Service helps you direct, manage, and monitor your organization's AI activities. It provides the tools organizations need to scale AI responsibly and efficiently. Simplify compliance processes, mitigate risks and streamline operations to build trust through transparency, save time with automation and enhance collaboration across teams.
Overview
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watsonx.governance overview
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watsonx.governance and Amazon SageMaker
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Manage and monitor your GenAI and ML models
Gen AI is driving many new use cases but also exposes businesses to new risks and complexities. As organizations leverage AI agents to drive growth, business leaders are under growing pressure to demonstrate ROI from their AI initiatives to remain competitive. To safeguard your business, a holistic governance approach is needed that effectively directs, manages, and monitors your AI activities
IBM watsonx.governance accelerates responsible, transparent, and explainable AI workflows by governing any AI--including models, applications, or agents--on one integrated platform. It provides governance throughout the AI lifecycle for models, apps or agents deployed anywhere. watsonx.governance provides organizations with the toolkit they need to govern both Gen AI and ML models, applications or agents in the following key areas:
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Lifecycle governance - automate and scale model governance, provide stakeholder visibility with customizable dashboards and reports while capturing model metadata with factsheets for effortless report generation.
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Compliance - manage compliance with the growing and changing AI regulations and industry standards.
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Risk management - monitor for fairness, bias, drift and key LLM metrics, proactively detect and mitigate risks based on pre-set thresholds.
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A dashboard provides insight into relevant information related to models, including a breakdown of use cases and models by status, change requests in process, challenges, issues and tasks assigned to the various stakeholders.
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Identify and manage AI risks early on with risk assessments at use case and model-level
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Monitor the effectiveness of models with metrics. Metric values are captured for each metric and a breach status is automatically calculated to indicate if the metric is red, yellow, or green.
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Automated workflow enables the review and approval of AI assets across stakeholders.
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Provide ability to record and assess AI Use case evidence for audit and compliance
For Premium pricing, customized pricing, or to request a demo, please contact us directly at: watsonx_on_AWS@wwpdl.vnet.ibm.comÂ
*Model evaluations are only available in Mumbai region
Highlights
- Evaluate and monitor multiple AI assets simultaneously across the AI lifecycle accelerating time to production. Save time through factsheets that automatically collect and document model metadata across the AI lifecycle while ensuring transparency.
- Manage AI risk early on with preset thresholds in AI systems to monitor for bias, drift and breaches in key LLM metrics and detect specific input/output content in real time.
- Access powerful governance, risk and compliance capabilities featuring workflows with automated approvals, customizable dashboards, risk scorecards and reports.
Details
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Delivery method
Deployed on AWS
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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
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Standard | Includes 1 Instance, model risk governance for 5 AI Use Cases, 25 concurrent users, 12000 evaluations | $36,000.00 |
Dimension | Cost/unit |
|---|---|
Use Case Overage | $15,000.00 |
Vendor refund policy
Please contact your client account team for refund information
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)Â .
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
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Sign in to open a new case or review existing cases: https://ibm.biz/watsonx-gov-aws-supportÂ
You can view, start, or contribute to watsonx.governance user discussions on the IBM Community. Find the watsonx.governance group here:
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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Customer reviews
0 ratings
0 AWS reviews
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47 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Banking
Model Module is flexible and sophisticated
Reviewed on Oct 08, 2025
Review provided by G2
What do you like best about the product?
continued support and development for the tool; flexibility and capabilities in workflow design
What do you dislike about the product?
does not have ability to natively link upstream/downstream models/objects together; limited in ability to link a Model Object to another Model Object (link objects of the same type)
What problems is the product solving and how is that benefiting you?
Ability to manage model inventory
Mark D.
Watsonx Governance
Reviewed on Oct 07, 2025
Review provided by G2
What do you like best about the product?
I like how watsonx governance combines model risk, generative ai, and governance. For example, the ability to create a use case, track a model, associate with workspaces, and evaluate prompts all in a single area are great. Even better, but IBM recently launched a new feature called the Governance Console where you can track multiple models, enable and create controls, and evaluate risks.
Governance had Gen AI metrics like ROUGE and BLEU, as well as the ability for classification like F1, Accuracy, precision, recall, etc
Governance had Gen AI metrics like ROUGE and BLEU, as well as the ability for classification like F1, Accuracy, precision, recall, etc
What do you dislike about the product?
I don't like how an evaluation in Watsonx Governance overwrites the previous evaluation results if done on the same day. OpenScale will keep the history, but governance in the AI Factsheet does not. Same issue exists for the trend charts.
For example, the trend charts available in OpenScale have a time setting for hourly, daily, weekly, etc. But let's say i do 20 evaluations in a day. Then a week later I want so show how those 20 evaluations did, and the overall trend. If I change to hourly, then the graph is too sparse (it's been a week), but if I change to daily, then it's just a single dot (all 20 evals were on a same day). Wish OpenScale and Governance would fix this.
Then the ability to show the generated_text against the reference (ground truth) text. Yes, you can download the results to a CSV but there's two big missing features (1) the downloaded CSV is missing the reference text, it only has the generated text. So you have to come up with a way to match that record to its original source if you want to compare, and (2) you have to do this each time for each subset. Why not just have the ability to view that record in the software and avoid having to download the CSV? the text is truncated and there's no way to see it
For example, the trend charts available in OpenScale have a time setting for hourly, daily, weekly, etc. But let's say i do 20 evaluations in a day. Then a week later I want so show how those 20 evaluations did, and the overall trend. If I change to hourly, then the graph is too sparse (it's been a week), but if I change to daily, then it's just a single dot (all 20 evals were on a same day). Wish OpenScale and Governance would fix this.
Then the ability to show the generated_text against the reference (ground truth) text. Yes, you can download the results to a CSV but there's two big missing features (1) the downloaded CSV is missing the reference text, it only has the generated text. So you have to come up with a way to match that record to its original source if you want to compare, and (2) you have to do this each time for each subset. Why not just have the ability to view that record in the software and avoid having to download the CSV? the text is truncated and there's no way to see it
What problems is the product solving and how is that benefiting you?
Model Governance and Monitoring
Computer & Network Security
Powerful AI Governance Tool for Cybersecurity Compliance and Risk Management
Reviewed on Oct 07, 2025
Review provided by G2
What do you like best about the product?
It gives us clear visibility and control over AI and data workflows, making it easier to enforce compliance and manage risk. I especially value its explainability features and how well it integrates with our cybersecurity processes.
What do you dislike about the product?
The UI can feel a bit complex at first, especially for new users. There’s a learning curve, and some advanced features could be more intuitive. But once you’re familiar with it, it’s a powerful tool.
What problems is the product solving and how is that benefiting you?
It helps us manage AI risk, ensure compliance with data privacy regulations, and maintain transparency in automated decisions. This reduces security gaps and saves time during audits and risk assessments.
Dr. Giulia S.
Governance product to face the EU AI Act
Reviewed on Oct 06, 2025
Review provided by G2
What do you like best about the product?
The product had matured greatly over the past year and offers access to a wide range of personas. This is extremely valuable since preparing the documentation for the EU AI Act is a team effort.
It is well integrated with Watsonx AI.
It is well integrated with Watsonx AI.
What do you dislike about the product?
Pricing tag.
Integration with Git can be improved.
Integration with Git can be improved.
What problems is the product solving and how is that benefiting you?
Monitoring AI models at different stages (from dev, test, production) and support for the EU AI Act requirements
Ratnesh R.
Review for IBM Watsonex.governance
Reviewed on Sep 12, 2025
Review provided by G2
What do you like best about the product?
Much needed framework for governing models applications and data workflows.
Responsible AI Framework
Automated Compliance
Responsible AI Framework
Automated Compliance
What do you dislike about the product?
Not much as of now. New to me .Cost can be reduced if feasible.
What problems is the product solving and how is that benefiting you?
Customized dashboards and model factsheet,simplifies documentation.