Zenitech

Zenitech is a technology services company that provides software development and technology implementation for organisations. The company is headquartered in the United Kingdom and maintains operations or offices in Lithuania, Romania and Hungary. Its activities include designing and building software systems, delivering data and analytics capabilities, and applying artificial intelligence and automation in client projects.

Services and Capabilities

• Custom software development: delivery of web applications, browser extensions and backend systems.
• Artificial intelligence and machine learning: development and deployment of ML models, AI agents and AI-augmented software development processes.
• Data strategy and analytics: enterprise data roadmaps, data platforms and analytics enablement for operational and business use cases.
• Systems integration and APIs: integration of disparate systems, real-time alerts and cross-system data flows.
• Automation and validation: automation of data validation processes and workflow automation to reduce manual work.
• Experimentation and research partnerships: testing and evaluation of emerging tools and libraries within a software development lifecycle.

Industry Focus

• Information & Communications Technology: development of connectivity and platform components, browser-based tooling and research-related integrations.
• Energy & Utilities (including oil & gas): predictive modelling and demand forecasting to support operational planning.
• Aviation, Automotive & Transportation: enterprise data strategy and analytics roadmaps for navigation and large-scale operational datasets.
• Banking and Financial Services: automation of data validation and other processes to improve operational accuracy.
• Public sector and education: projects that support access to academic content and research integrity.

Technology and Delivery Approach

• Applied integration of data platforms, APIs and browser-based components to connect information sources and user interfaces.
• Use of machine learning models and predictive analytics for demand forecasting and decision support.
• Development of reusable AI components and agent libraries used as building blocks in custom AI solutions.
• Incorporation of AI tools into the software development lifecycle to automate parts of development and testing.
• Delivery through iterative experimentation, prototyping and implementation phases to validate technical approaches before scale-up.