Overview
IBM watsonx.governance overview
Govern generative AI and ML models, evaluate and monitor for model health, accuracy, drift and bias, and access powerful governance, risk and compliance capabilities.
IBM watsonx.governance overview
Monitor AI models with Amazon SageMaker
Direct, manage, & monitor your GenAI and ML models
Governing Amazon SageMaker AI Lifecycle
AI can transform business operations by driving efficiency and unlocking new opportunities. However, scaling AI introduces significant challenges related to governance, compliance and risk management. The stakes are high. Not complying with complex regulations can result in lengthy audits and costly fines. Moreover, reliance on manual tools can introduce errors and delays in your AI deployment cycles.
IBM watsonx.governance is an enterprise-ready AI governance toolkit designed to accelerate responsible AI workflows by governing any AI including models, applications or agents. It integrates seamlessly with existing systems, empowering businesses to adopt AI at scale. Moreover, it prepares you to meet regulatory requirements while optimizing costs. The key areas that watsonx.governance addresses are:
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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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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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Compliance - Simplify compliance by translating external AI regulations into enforceable policies that are automatically applied across systems.
For custom configuration and pricing please contact watsonx_on_AWS@wwpdl.vnet.ibm.comÂ
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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Features and programs
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Pricing
Dimension | Cost/12 months |
---|---|
IBM watsonx.governance starting configuration | $441,600.00 |
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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
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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