Overview
watsonx.governance overview
Govern AI. Scale responsibly. Simplify regulatory compliance process globally.
watsonx.governance overview
watsonx.governance and Amazon SageMaker
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
Unlock automation with AI agent solutions

Features and programs
Financing for AWS Marketplace purchases
Pricing
| 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 | 
The following dimensions are not included in the contract terms, which will be charged based on your usage.
| Dimension | Cost/unit | 
|---|---|
| Use Case Overage | $15,000.00 | 
Vendor refund policy
Please contact your client account team for refund information
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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.
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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
Model Module is flexible and sophisticated
Watsonx Governance
Governance had Gen AI metrics like ROUGE and BLEU, as well as the ability for classification like F1, Accuracy, precision, recall, etc
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
Powerful AI Governance Tool for Cybersecurity Compliance and Risk Management
Governance product to face the EU AI Act
It is well integrated with Watsonx AI.
Integration with Git can be improved.
Review for IBM Watsonex.governance
Responsible AI Framework
Automated Compliance
