Privacy Engineering, AI, Data & Cloud Services

Explore our comprehensive services in privacy engineering, agentic AI, data analytics, and cloud software architecture. Learn how CODEVIA's expertise can transform your business with secure, scalable, and privacy-first solutions.

Expert Privacy & Data Solutions

Our team combines hands-on industry experience with practical privacy delivery. We focus on privacy policy generation, cookie policy generation, privacy risk audits, and privacy-aware implementation work that is both technically sound and business-focused.

Illustration of CODEVIA privacy engineering and AI consultancy services

Privacy Engineering: Building Trust Through Technical Excellence

Privacy isn't just about compliance—it's about building trust with your users and creating sustainable business practices. Our privacy engineering services help you integrate privacy considerations into every aspect of your technology stack, from system architecture to user interfaces.

  • Privacy-by-Design architecture and implementation
  • GDPR, CCPA, and international privacy regulation compliance
  • Data Subject Rights (DSR) automation systems
  • Privacy impact assessments and risk mitigation
  • Secure data processing and anonymization techniques

Our approach is grounded in practical implementation and clear governance. We help teams create and maintain privacy policies, cookie policies, and risk assessments that align with real product and data flows.

Whether you're launching a new product or improving an existing one, we design solutions that protect user data while enabling your business to thrive. Our experience spans web applications, mobile platforms, and enterprise systems across industries from fintech to healthcare.

AI Engineering & Agentic Systems: Production-Ready AI for Real Workflows

We also help teams apply AI in practical, high-value ways. Our agentic AI consultancy focuses on building assistants that can support engineering and operational workflows with the right tools, context, and guardrails.

  • Designed and implemented an agentic AI assistant platform using Python, LangGraph, and Chainlit
  • Built modular MCP server integrations for GitHub, PostgreSQL, and Grafana
  • Implemented prompt orchestration, tracing, and evaluation workflows to improve reliability and observability
  • Enabled tool-augmented, context-aware LLM interactions for engineering teams

The result is AI that is more than a demo: it is measurable, maintainable, and useful in day-to-day operations.