MLCode

Contact for Pricing

Automate AI data security across environments with HexaKube technology.

About

MLCode delivers a specialized platform aimed at strengthening the data security framework for organizations heavily leveraging artificial intelligence and machine learning solutions. Its central offering, HexaKube, integrates advanced security controls designed to detect, monitor, and address vulnerabilities across all stages of data management—whether information is being stored, accessed, or transmitted.

The system employs automation to facilitate proactive management of potential threats, reducing the burden of manual oversight on IT and data teams. By providing ongoing visibility into data movement and system access, MLCode empowers organizations to swiftly identify risky behavior and address security gaps before they become serious incidents.

HexaKube’s adaptability allows it to be deployed across a variety of IT landscapes, such as public clouds, private data centers, and hybrid arrangements, making it suitable for businesses operating under complex infrastructure requirements. Its features support compliance and risk management for sectors with demanding data protection standards.

Who is MLCode made for?

CTO / Head of Engineering Legal / Compliance Officer IT Manager / Systems Admin
Established company (101-250 people) Large company (251-1000 people) Enterprise (1000+ people)

MLCode is particularly suited for technical executives, security officers, IT administrators, and compliance managers working in organizations where large-scale AI or machine learning initiatives handle sensitive data.

Enterprises in finance, healthcare, research, and sectors bound by strict regulatory mandates will benefit most, especially those requiring automated monitoring and robust protection of datasets spanning multiple environments—including cloud and on-premises systems.

This platform is relevant for teams responsible for setting data governance policies, managing cybersecurity risks, and ensuring regulatory compliance in the deployment of AI models. It is ideal when organizations need to continuously track data access and movement in real-time, respond to emerging threats, and resolve security incidents efficiently across diverse digital ecosystems.