The power of GenAI for application modernisation

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The power of GenAI for application modernisation The power of GenAI for application modernisation The power of GenAI for application modernisation

The challenge

Many companies continue to run their business relying on applications that are functionally complete but technologically outdated, difficult to evolve due to lack of expertise and ever-increasing maintenance costs. Modernising these applications is becoming an increasingly strategic priority, but it is also necessary to keep costs, timelines and risks under control.

GenAI has made it possible to address modernisation in a faster, safer and more efficient way.

Fincons has seized this opportunity by creating a migration engine that automates and accelerates both code and architecture transformation, to deliver high-performance, technologically advanced applications while drastically reducing project time and cost.

Challenge - GenAI

Fincons’ approach

A robust combination of expertise, tools, and methodologies

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Know-how Know-how
  • GenAI tools and LLM models
  • Technologies and frameworks for both source and target applications
  • Prompt engineering
Migration engine Migration engine
  • Semi-automated, iterative migration
  • Ability to implement different GenAI technologies
  • Capable of handling various source and target architectures
  • Automatic generation of readable code, technical documentation and test cases
  • Ability to use the client’s own frameworks, patterns and components
Methodology Methodology
  • Structured approach, organised in phases that cover the project’s entire lifecycle

The engine for application modernisation

The engine that industrialises and optimises the use and effectiveness of GenAI, capable of working with any LLM model.

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Scan Scan

Source code anlysis, cleansing and grouping files into units to be transformed

Prompt customisation Prompt customisation

Adaptation of GenAI prompts for optimal code conversion

“As-is” application documentationn “As-is” application documentation

Reverse engineering and production of the functional and technical documentation of the current state

Code conversion & generation Code conversion & generation

Conversion of source code via GenAI APIs and generation of target code structure

Documentation & test cases Documentation & test cases

Generation of code with comments, documentation and test cases

Testing & KPI measurement Testing & KPI measurement

Testing, running source and target systems in parallel, comparing outputs, validating the target, and measuring KPIs for conversion effectiveness

Methodology

A structured plan to deliver successful projects

Methodology
Methodology
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Objective definition
Objective definition

Defining: migration type, target application architecture, target technical architecture and testing strategy

Assessment of existing source application
Assessment of existing source application

Analysing the structure of the source application, categorising source files by type and role, analysing application flows and most representative use cases, reviewing code practices, patterns and best practices, producing automated “as-is” documentation

Definition of target architecture
Definition of target architecture

Defining target architecture (e.g. monolithic vs modular), defining the target frameworks and patterns, determining back-end API granularity, logical mapping between each category of source file and target components

Engine configuration
Engine configuration

Configuring the migration engine for the specific context, designing GenAI prompts based on mapping between source and target components and the required transformations, integrating the new GenAI prompts into the engine

Iterative approach
Iterative approach

A pilot project on a representative code base, with optimisation based on pilot results and successive iterations

Migration
Migration

Cleansing source code and gathering statistics on code usage to avoid migrating unnecessary elements, migrating source code over the entire affected code base, testing, monitoring KPIs and refining the migrated code through successive iterations

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Benefits

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Efficiency Efficiency

Significant reduction in effort, duration, and cost of migration projects, increasing the sustainability of application modernisation initiatives

Massive, iterative approach Massive, iterative approach

The same code may be migrated multiple times during the project, allowing for incremental adjustments and improvements, which usually depend on the architecture and design of the source application

Measurability Measurability

The GenAI-assisted approach allows for qualitative success KPIs to be defined and measured throughout the project, as an integral part of DevOps processes

Transformative migration Transformative migration

The GenAI-assisted approach enables not only code translation and migration but also transformation of architecture, structure, and technical documentation of the application, making its maintenance easier

Discovery intelligence Discovery intelligence

Rapid and simplified evaluation of source application code, leading to reductions in time and effort during analysis phases

Why Fincons

Why Fincons

We are an international IT business consulting and system integration company that has been assisting clients for over 40 years in identifying the opportunities of digital transformation, providing innovative technologies and solutions to better face the future.

With our dedicated Technology Innovation Hub, we have invested in the study and application of GenAI technologies, gaining considerable expertise and delivering successful projects.

We also rely on more than 2,500 highly qualified professionals, spread across Italy, Switzerland, the UK, Germany, Belgium, France, the US and India, and on a highly flexible hybrid delivery model that combines professionals working on-site at client locations supported remotely by the Group’s Delivery Centre, to guarantee quality and competitiveness.