Adeptiv AI provides a unified platform for automated AI governance, risk management, and compliance tracking. The system manages the entire AI lifecycle from inventory to real-time risk detection and documentation. This solution helps enterprises adhere to evolving global regulations like the EU AI Act and NIST AI RMF in an auditable manner.
Funding
$100K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises deploying multiple AI and generative AI models often lack a unified inventory, rely on manual spreadsheets for compliance, and face fragmented oversight across legal, risk, and engineering teams. This results in regulatory exposure, hidden bias, audit failures, and delayed product releases.
Solution
Adeptiv AI delivers an enterprise‑grade AI governance platform that automatically discovers and catalogs all AI assets across on‑prem, cloud, and hybrid environments. The system maps each model, dataset, and use case to more than 30 global regulations—including the EU AI Act, NIST AI RMF, and ISO 42001—generating real‑time risk scores and bias metrics. Integrated explainability tools (e.g., SHAP, LIME) produce model cards and evidence packs that satisfy audit requirements without manual effort. Continuous monitoring flags drift, fairness violations, and security anomalies, while role‑based workflow engines enforce policy approvals and remediation actions. The platform offers out‑of‑the‑box connectors to data warehouses, feature stores, MLflow, GitHub, Snowflake, Databricks, and enterprise identity providers, enabling seamless integration into existing MLOps pipelines. Both SaaS and on‑prem deployments provide data‑residency options for highly regulated sectors, turning governance from a bottleneck into a scalable, auditable process.
Target Audience
Primary users are AI engineering and risk/compliance teams in regulated enterprises—such as finance, healthcare, and public‑sector organizations—that need to operationalize AI governance at scale.
Features
- Automated AI inventory discovery across code repositories, data lakes, and model registries, creating a searchable catalog with metadata and lineage.
- One‑click regulatory mapping to 30+ standards, with auto‑generated compliance artifacts and impact‑assessment templates.
- Contextual risk scoring and bias/fairness testing using cohort analysis and statistical parity metrics, coupled with remediation recommendations.
- Explainability engine that produces model cards, SHAP/LIME visualizations, and versioned documentation for each deployment.
- Real‑time monitoring dashboard with drift detection, alerting, and KPI visualizations for model performance and compliance posture.
- Policy automation and role‑based workflow engine for approvals, evidence collection, and audit‑ready reporting.
- Native integrations with Snowflake, Databricks, MLflow, GitHub, S3, Okta, and enterprise SIEMs for end‑to‑end MLOps governance.
- Optional on‑prem and private‑cloud deployments to meet strict data‑sovereignty requirements.