Matix and cloud migrations: greater control and up to 50% cost efficiency

Cloud migrations remain one of the most complex challenges within technology modernisation processes. They involve multiple systems, hard-to-track dependencies, critical architectural decisions, and a significant amount of manual effort. They are also often approached with incomplete or outdated documentation, which increases both the risk and the duration of projects.

Matix, as a platform based on multi-agent systems, provides a way to address this context by structuring migration as an organised, traceable and progressive process, combining advanced automation with expert validation at every stage.

Matix is a multi-agent system that distils Mática’s knowledge and experience into a virtual development and migration team. Its design replicates the different professional roles involved in the software lifecycle and in cloud migration projects, organising them in a structured and coordinated way.

Each agent represents a specific role and performs a defined function within the process. This initial set of agents is extensible and adaptable, allowing its behaviour to be tailored to different technological and organisational contexts.

✻ The Matix Product Owner translates project needs into clear user stories and well-defined acceptance criteria, applying frameworks such as INVEST to reduce ambiguity from the outset and ensure that each task has a specific and measurable objective.

✻ The Matix Designer defines the target architecture, the dependencies between components, and the implementation or migration strategy. They identify reusable elements and propose diagrams or pseudocode that serve as the foundation for technical execution.

✻ The Matix Coder implements tasks following the defined design. They produce clean, documented and tested code, and handle both migration and the refactoring of code and data, working directly on the relevant repositories.

✻ The Matix Reviewer validates the quality of the output, checks compliance with standards, performance and code readability, and verifies data validation criteria before preparing the Pull Request for approval.

✻ The Matix Supervisor carries out in-depth analysis of code and systems, generates detailed documentation, and acts as a reference point for resolving questions across one or multiple repositories. They also coordinate collaboration between agents and ensure overall process coherence.

All agents collaborate with one another, generating deliverables and continuously feeding back into the process. The human team intervenes at key points — validations, adjustments and complex decisions — always retaining control over the final outcome.

In Matix, migration is organised into two main areas of work: planning and execution, which are not treated as separate phases, but as parts of a single continuous flow.

During the planning phase, the migration roadmap is built and existing systems are analysed. This work produces a central artefact that acts as a reference point for the entire process. From there, technical execution builds on this prior knowledge, avoiding disconnected decisions or unnecessary rework.

This approach ensures that every technical action is supported by clear and up-to-date context.

Before migrating, it is essential to understand what existing systems actually do. Matix approaches this phase through a semi-automated discovery and documentation process, coordinated by the Supervisor Agent, which orchestrates the work of the different specialised agents.

At this stage, sub-agents such as DeepResearch and CodeExplorer are involved, analysing pipelines, processes, code repositories, configurations and technical dependencies. This analysis makes it possible to reconstruct how systems actually operate, even in environments where documentation is missing or unreliable.

The result is a clear view of the current state, including:

• end-to-end data flows,

• dependencies between systems and services,

• implemented business logic,

• technology stack and libraries in use.

All this information is consolidated into living documentation, which becomes the foundation for subsequent decisions within Matix.

During the analysis, Matix does not simply describe the current state. The agents also identify technical inefficiencies and opportunities for improvement, such as redundant processes, outdated code or potential performance optimisations.

This is where the PO Agent comes into play, responsible for prioritising these improvements based on their impact, the required effort and the expected business value. This enables pragmatic decisions about which optimisations to address during the migration and which to defer to later stages, avoiding unnecessary project overload without a clear return.

In this way, migration becomes a controlled opportunity to introduce improvements without losing sight of the main objectives.

Once the use cases have been prioritised, Matix moves on to designing the target architecture. This task is led by the Designer Agent, responsible for defining the migration strategy and selecting the most appropriate cloud services for each scenario.

The Designer Agent takes into account aspects such as scalability, security, resilience and costs, and proposes an architecture aligned with both technical and business needs. All proposals go through human validation, ensuring that architectural decisions align with the organisation’s standards and experience.

The infrastructure is defined from the outset using Infrastructure as Code (IaC), making it easier to deploy, evolve and maintain over time.

Technical execution is primarily handled by the Coder Agent, responsible for bringing the defined architecture to life. This agent generates infrastructure templates, configures CI/CD pipelines and performs refactoring tasks when required.

Thanks to its multi-repository capabilities, the Coder Agent can work in parallel across source and target systems, run comparisons and ensure consistency between both environments. Although many tasks are automated, critical deployments and changes are reviewed and validated before proceeding, maintaining control over production environments.

In Matix, validation is not concentrated at the end of the project. Throughout execution, agents perform continuous checks between migrated and original systems, detecting deviations at an early stage.

The process is organised into iterations that include:

1. Phase planning
2. Technical execution
3. Cross-validation between source and target
4. Monitoring and subsequent adjustments

The Supervisor Agent coordinates these iterations, ensuring that the process progresses in an organised manner and that the information generated at each step is incorporated into the overall project knowledge.

The use of agents makes it possible to automate a large part of repetitive and structured technical work, reducing time and manual errors. However, Matix does not remove the role of human teams, but rather repositions it.

People continue to play a role at the points where context, experience and business knowledge are critical: defining priorities, validating architectural decisions and approving outcomes. Automation brings speed and consistency; human judgement brings direction and control.

Mática’s approach with Matix uses generative AI technologies and agents as a lever for efficiency, automating repetitive tasks and freeing up senior human teams to focus on control, validation and higher-value decisions.

This model has already been applied both in internal processes and in client projects, always under a clear principle: AI acts as support, not as a substitute, and does not take control of the code.

In terms of results, Matix has enabled the automation of more than 80% of Java migration tasks and over 70% in Spark environments, including migrations from Scala to PySpark. This has led to a reduction in overall manual effort of over 85%.

In addition, more than 10 million lines of code currently in production have been migrated, achieving improvements of up to 50% in cost efficiency thanks to process and architecture optimisation.

Matix does not promote an uncontrolled development model or “vibe coding”. Automated code generation is always subject to review, validation and approval. AI is integrated as another element within technological transformation, bringing speed and consistency without replacing professional judgement.

Cloud migrations often fail not due to a lack of tools, but because of a lack of structure, visibility and control. Matix addresses these challenges by structuring migration as a governed, end-to-end process, supported by specialised agents and continuous expert validation.

The result is a more predictable migration, with reduced manual workload and a stronger focus on decisions that truly add value, transforming a traditionally complex process into a more controlled and sustainable exercise.

At Mática Partners, we are helping organisations apply Matix to real cloud migration projects through controlled pilots and initial assessments of legacy systems.

If you would like to explore how to reduce risk, accelerate timelines and optimise costs in your next migration, we would be happy to discuss it with you.