AI Trust Center
As an AI implementation partner, we build solutions with security and reliability in mind, applying industry standards and best practices throughout development. This page walks through how we deliver on that – from architecture and LLM guardrails to data protection and our ISO 27001-certified information security management system. Whether you’re evaluating us as a partner or scoping a new initiative, this is where you’ll find the answers you need.
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In the current landscape of rapid AI adoption, many initial Proofs of Concept (PoCs) are often built quickly, prioritizing speed-to-demo over robustness and security. However, transitioning from a sloppy PoC to a production-grade AI application reveals a critical gulf. A successful, real-world agentic AI application requires far more than just a functional model.
The foundation of a reliable production solution rests on several pillars: high-quality data processing architecture, meticulous data protection, and secure, accurate model usage. This includes the rigorous selection of the correct model and provider, sophisticated flow design to ensure efficacy, and, most importantly, security by design. For us, this means architecting solutions where AI models are strictly prohibited from directly accessing sensitive data, ensuring that core data protection is inherent to the system, not an afterthought. This disciplined approach is essential for any successful, enterprise-ready AI deployment.
Bogdan Sergiienko
CTO
How We Protect Your Data and AI Solutions
Data Protection & Access Control
Data protection and access control practices are shaped by the specific requirements of each client engagement.
When a solution is hosted within our infrastructure, we apply a combination of technical, organizational, and operational security measures like encryption at rest and in transit, enforce role-based access control (RBAC), segregation of environments, and follow the principle of least privilege across all environments.
Secure Software Development Lifecycle
We uphold industry-standard secure development practices to ensure security is embedded throughout the development process. Code undergoes review and dependency vulnerability scanning, and solutions are subject to application security testing to identify and remediate potential vulnerabilities before deployment.
To address AI-specific risks, our development lifecycle includes targeted security testing of AI components, with a focus on the risks defined in the OWASP Top 10 for LLM Applications.
Incident Management
Our incident management approach is established in line with ISO 27001, with defined roles, reporting channels, and incident handling procedures in place. In the event of an incident, clients are notified promptly in accordance with the terms of our agreements and applicable SLAs.
Regular Security Training
Routine information security awareness training, covering current security and AI risks and responsibilities, is provided to personnel. Engineering roles receive additional training focused on secure development practices and LLM-specific risks.
Secure Cloud Architecture
Cloud architecture decisions are driven by client context – their hosting preferences, compliance obligations, and operational model.
When a solution is hosted within our infrastructure, we leverage cloud-native security services and best practices to protect infrastructure and data, including network isolation, segregation of environments, access controls, and encryption. Cloud environments are regularly monitored for misconfigurations, and vulnerability scans are performed to pinpoint and mitigate potential threats. Infrastructure logging is configured to provide a baseline audit trail across cloud environments.
LLM Safety & Guardrails
We don’t bolt security onto AI as an afterthought – we build it in from day one. Our engineers actively harden every LLM-powered solution against prompt injection, jailbreak attempts, and sensitive data leakage, combining purpose-built guardrails at input and output with retrieval-layer access controls that ensure users only ever see data they’re permitted to access. We continuously monitor LLM activity for anomalous patterns, feeding alerts directly into our incident response process so threats are caught and contained fast.
When working with third-party model providers, we push for zero-retention API configurations and validate their data handling standards against our clients’ compliance requirements, not just our own. The result is AI you can deploy with confidence, not crossed fingers.
We red-team our LLMs the same way attackers will – with patience, creativity, and no assumptions about what the model won’t do. Every guardrail we ship has been stress-tested against the scenarios most teams only discover after an incident. We don’t wait for the breach to understand the risk.
Anhelina Biliak
Application Security Lead
ISO-Certified Information Security Management System
Master of Code Global holds an ISO/IEC 27001:2022 certificate. Our certification scope explicitly includes the development and support of AI-powered software solutions and AI consultancy.
Our AI Technology Toolkit
We translate your data security requirements into a technical architecture designed to protect them. Throughout our development lifecycle, we enforce code reviews, continuous vulnerability scanning, and security testing aligned with OWASP Top 10. For hosted solutions, we apply cloud-native security services and best practices to protect infrastructure and data across different layers – including the project’s data isolation, segregation of environments, access controls, encryption, logging, and continuous infrastructure monitoring.
Iryna Shevchuk
Information Security Officer
Frequently Asked Questions
How do you ensure the security of the client's data?
The security of your solution is defined by your unique requirements and compliance needs. When a solution is hosted on our side, we protect client data through a combination of technical, organizational, and operational measures, aligning our practices with industry standards like the ISO 27001 framework. These include, in particular, access controls, isolated environments, encryption, secure development practices, and security monitoring.
How do you implement data segmentation to ensure isolation between different customers?
We deploy separate, dedicated infrastructure and isolated environments for each client engagement.
Do you support client-specific requirements for data residency, processing, and retention?
Yes. As your software development provider, we can set up environments configured per your needs. This includes the ability to select specific geographical regions for deployment and configure particular retention settings to ensure your data residency, processing, and retention practices are compliant with your internal standards and relevant regulatory requirements.
How do you address risks related to AI outputs, such as bias, inaccuracies, or hallucinations?
We may apply different strategies like RAG architecture, pre-generation, and fine-tuning to minimise the risks. You can read more about our approach to LLM security here.
Do you perform security testing for the AI solutions you build?
Yes. We have a dedicated Application Security team that performs code review and solution testing to identify vulnerabilities. This comprises specialized checks for AI-specific risks, aligned with the OWASP Top 10 for LLM Applications.
Can you implement specific security, privacy, or compliance requirements for the client’s project?
Yes, сustomization is fundamental to our service. A client defines their precise specifications, and our team translates these into the technical architecture and code. This commitment ensures that the final solution aligns with the client’s corporate standards, legal, and regulatory obligations.
Do you provide maintenance and support services after solution development?
Yes, we provide support and maintenance services. The scope of these services is defined per client’s specific operational needs and requirements.
How is client data handled at the end of the contract?
Upon contract termination, we transfer environments and the client’s data to the client.
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