Deeploy

About Deeploy

Deeploy is an enterprise-grade AI Governance platform engineered to provide centralized oversight, compliance, and monitoring for all AI systems within an organization. It serves as the critical governance infrastructure for technology, risk, and compliance teams managing complex AI portfolios. The platform is designed to address the operational and regulatory challenges that arise when deploying AI at scale, particularly in light of stringent frameworks like the EU AI Act. Deeploy enables complete visibility and control by allowing organizations to discover, onboard, and manage every AI model—whether built on traditional MLOps or modern Generative AI platforms—from a single interface. Its core value proposition lies in transforming governance from a theoretical burden into an enforceable, automated, and integrated practice. By offering real-time explainability, human feedback loops, automated audit trails, and guided control frameworks, Deeploy significantly reduces operational and compliance risks. This ensures that organizations can accelerate AI innovation and scaling while maintaining rigorous oversight, proving compliance, and building trust with stakeholders and regulators.

Features of Deeploy

AI Discovery and Onboarding

This feature provides complete visibility across an organization's AI landscape. It enables the discovery, onboarding, and centralized management of every AI system from a single interface. The platform connects to any existing MLOps or GenAI platform, eliminating blind spots without requiring costly and disruptive migrations. This creates a unified AI inventory and documentation hub, which is the foundational step for any governance program, ensuring no AI initiative operates outside of oversight.

Control Frameworks

Deeploy offers structured workflows to navigate complex AI regulations with confidence. Organizations can select from default, pre-configured control frameworks such as ISO 42001 and the NIST AI RMF, or build custom frameworks tailored to internal policies. The system guides users through AI system risk classification in minutes and establishes clear accountability with formal approval processes. This feature translates regulatory text into actionable, organizational-specific governance structures.

Control Implementation

This feature turns governance frameworks into enforceable, engineer-friendly controls. It automatically assigns the correct requirements to each AI system based on its risk profile, eliminating manual, error-prone work. Engineers receive clear, actionable tasks, while compliance is accelerated by up to 90% through the use of templates and automatically collected evidence. AI-powered assessments further handle repetitive compliance verification work, ensuring governance is practically adhered to.

Real-Time Monitoring

Deeploy provides proactive surveillance of AI performance in production. It monitors for critical issues like model drift, performance degradation, and output anomalies in real-time, sending instant alerts to prevent incidents before they impact users or create compliance breaches. The feature includes capabilities for adding tracing and guardrails to protect Large Language Model (LLM) outputs, ensuring continuous operational integrity and risk mitigation.

Use Cases of Deeploy

Achieving EU AI Act Compliance

Organizations subject to the EU AI Act utilize Deeploy to systematically classify AI systems by risk level, implement required controls, and generate the necessary documentation and audit trails. The guided workflows and automated evidence collection streamline the compliance process, ensuring all high-risk AI applications meet transparency, robustness, and human oversight requirements efficiently and demonstrably.

Centralizing Oversight for Fragmented AI Portfolios

Enterprises with AI models scattered across different teams, vendors, and embedded systems use Deeploy to gain a single source of truth. The discovery and onboarding feature creates a centralized registry, allowing governance teams to finally see everything that is running, assess aggregate risk, and apply consistent policies, thereby transforming a chaotic "jungle of AI systems" into a managed portfolio.

Enabling Safe LLM and GenAI Deployment

Companies implementing Generative AI applications deploy Deeploy to add essential governance layers. The platform provides real-time monitoring and guardrails for LLM outputs to prevent harmful, biased, or non-compliant content. It also facilitates human-in-the-loop feedback mechanisms, allowing experts to review and correct outputs, which is critical for sensitive sectors like healthcare or financial services.

Accelerating Model Deployment with Governance-by-Design

ML teams use Deeploy to integrate governance directly into the deployment pipeline. By providing clear requirements and automated compliance checks from the start, it reduces the traditional friction between development and compliance teams. This allows data scientists to deploy models in hours instead of weeks, with built-in explainability and monitoring ready for production from day one.

Frequently Asked Questions

What types of AI systems can Deeploy manage?

Deeploy is platform-agnostic and designed to manage a wide spectrum of AI systems. This includes traditional machine learning models from MLOps platforms (e.g., MLflow, SageMaker), Generative AI applications built on frameworks like LangChain, and AI embedded within third-party vendor software or internal applications. Its flexible onboarding connects to these systems without requiring migration.

How does Deeploy help with auditability and evidence collection?

The platform automates the collection and logging of critical evidence required for audits. This includes records of model versions, performance metrics, risk classifications, approval decisions, human feedback interactions, and monitoring alerts. All data is stored in a centralized, immutable audit trail, making it straightforward to generate compliance reports for internal or external regulators.

Can we customize governance frameworks to match our internal policies?

Yes. While Deeploy offers pre-built templates for major standards like ISO 42001 and the NIST AI RMF, it is fully customizable. Organizations can define their own control frameworks, risk categories, approval workflows, and evidence requirements to align perfectly with unique internal governance, risk, and compliance (GRC) policies and industry-specific regulations.

How does the real-time monitoring and alerting work?

Deeploy's monitoring engine continuously tracks predefined metrics and thresholds for each deployed AI model. It uses techniques to detect statistical drift, significant drops in accuracy or performance, and anomalous output patterns. When a threshold is breached, the system triggers instant alerts via integrated channels (e.g., email, Slack) to designated teams, enabling swift investigation and remediation.