Amazon SageMaker
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers.
Learn more
OneTrust Privacy Automation
Go beyond compliance and build trust through transparency, choice, and control. People demand greater control of their data, unlocking an opportunity for organizations to use these moments to build trust and deliver more valuable experiences. We provide privacy and data governance automation to help organizations better understand their data across the business, meet regulatory requirements, and operationalize risk mitigation to provide transparency and choice to individuals. Achieve data privacy compliance faster and build trust in your organization. Our platform helps break down silos across processes, workflows, and teams to operationalize regulatory compliance and enable trusted data use. Build proactive privacy programs rooted in global best practices, not reactive to individual regulations. Gain visibility into unknown risks to drive mitigation and risk-based decision making. Respect individual choice and embed privacy and security by default into the data lifecycle.
Learn more
MintMCP
MintMCP is an enterprise-grade Model Context Protocol (MCP) gateway and governance platform that provides centralized security, observability, authentication, and compliance controls for AI tools and agents connecting to internal data, systems, and services. It lets organizations deploy, monitor, and govern MCP infrastructure at scale, giving real-time visibility into every MCP tool call, enforcing role-based access control and enterprise authentication, and maintaining complete audit trails that meet regulatory and compliance needs. Built as a proxy gateway, MintMCP consolidates connections from AI assistants like ChatGPT, Claude, Cursor, and others to MCP servers and tools, enabling unified monitoring, blocking of risky behavior, secure credential management, and fine-grained policy enforcement without requiring each tool to implement security individually.
Learn more
Golf
GolfMCP is an open source framework designed to streamline the creation and deployment of production-ready Model Context Protocol (MCP) servers, enabling organizations to build secure, scalable AI-agent infrastructure without worrying about boilerplate. It allows developers to define tools, prompts, and resources as simple Python files, after which Golf handles routing, authentication, telemetry, and observability, so you focus on logic, not plumbing. The platform supports enterprise authentication (JWT, OAuth Server, API key), automatic telemetry, and a file-based structure that eliminates decorators or manual schema wiring. With built-in utilities for LLM interactions, error logging, OpenTelemetry integration, and deployment tools (such as a CLI with golf init, golf build dev, golf run), Golf provides a full stack for agent-native services. Included also is the Golf Firewall, an enterprise-grade security layer for MCP servers that enforces token validation.
Learn more
