Adeptiv AI - AI Governance
Your AI Governance Co-Pilot
Adeptiv AI tackles the messy reality of enterprise AI governance with automated discovery and compliance tracking. It crawls through your infrastructure to find every model, dataset, and pipeline you didn't know existed. Then builds a searchable catalog that actually makes sense.
Risk scoring happens automatically based on system impact. High-risk models get flagged with guided mitigation steps that won't leave your compliance team guessing. Bias testing runs cohort-based analysis. Spits out specific remediation recommendations.
Model cards generate themselves. Complete with data lineage. SHAP explanations. Limitation notes.
One-click mapping covers 28+ AI regulations including the EU AI Act and NIST frameworks. Your Chief AI Officer dealing with regulatory audits can export evidence packs and generate regulator-ready reports without manual document hunting. Say you're running credit scoring models across multiple regions — Adeptiv AI monitors for drift and bias while maintaining immutable audit logs that regulators actually want to see.
Adeptiv AI connects to Snowflake, Databricks, MLflow, and other enterprise tools you're already using. Role-based workflows handle sign-offs and human review gates without breaking your existing processes. Though the extensive automation means you'll need staff who understand AI governance principles rather than just compliance checkbox-ticking. Drift detection and compliance dashboards give you real-time visibility into model behavior across your entire AI portfolio.
It crawls through your entire infrastructure automatically -- scanning connected systems like Snowflake, Databricks, and MLflow. The discovery engine finds models, datasets, and pipelines that aren't documented anywhere. You'll often discover 3-5x more AI assets than what's officially tracked in spreadsheets or wikis.
Yep, it maps compliance requirements across 28+ regulations at once. Running credit scoring in both the EU and US? It'll track EU AI Act requirements alongside NIST frameworks automatically. The system generates separate compliance reports for each jurisdiction -- no need to manage multiple tracking systems.
It does cohort-based analysis to catch statistical bias across different demographic groups. Tests for disparate impact and equal opportunity violations too. When bias shows up, you get specific remediation steps (not just vague warnings about fairness issues).
They've got complete data lineage showing where training data came from and how it was processed. SHAP explanations break down feature importance for individual predictions. Each card also documents known limitations and performance boundaries -- which auditors specifically look for.
It flags high-risk models but doesn't automatically block deployment. The platform gives you guided mitigation steps and requires human sign-offs through role-based workflows. Your teams still control deployment decisions -- but they can't claim they didn't know about the risks.
It sends alerts through your existing notification systems. Logs the drift event in immutable audit trails too. The platform tracks both statistical drift and performance degradation over time -- then gives you specific recommendations on whether to retrain, adjust thresholds, or take the model offline.
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