AI-Assisted Legacy Refactor

AI-Powered Legacy Modernization

Accelerate modernization with AI that reviews legacy code
at scale, highlights what to fix first, and generates refactor suggestions aligned
with your architecture standards.

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AI-Driven, Expert-Led Refactoring

We leverage AI capabilities, supervised by our expert engineers, to analyze,
transform, and improve your legacy code at scale.

AI-Powered Modernization

AI-Powered Modernization

We use AI, guided by expert engineers, to analyze and modernize your legacy codebase at scale.

Save Time on Development

Save Time on Development

AI tools augment developers by spotting issues, suggesting rewrites, and generating refactored code snippets.

Improve Code Security

Improve Code Security

AI models trained on large corpora flag common anti-patterns and vulnerabilities before they become a threat.

Reduce Maintenance Load

Reduce Maintenance Load

By removing dead code, replacing deprecated APIs, and refactoring complex methods, we leave you with less code legacy to maintain.

Expert Supervision

Expert Supervision

Our engineering experts guide and validate every AI-driven change to ensure accurate, high-quality refactors.

Accelerate QA & Reviews

Accelerate QA & Reviews

AI-generated unit tests and suggested diffs lead to shorter QA reviews and less redundant code.

Safe, AI-Driven Modernization

Our Services Playbook

A structured, low-risk path to modernize legacy systems with AI.
Always guided by expert engineers.

Incremental Modernization

Use AI to propose micro-refactors and remove legacy code. Ship tight, reviewable PRs for fast, low-risk wins.

Risk-Based Prioritization

Use AI to beat complexity. We target low-risk, high-impact changes first, saving complex items for safer rollouts.

Test-Driven Refactoring

Lock in safety first. We use AI to generate unit tests and enforce CI gates that catch regressions automatically.

Our Approach

  • 01

    Incremental Modernization

  • 02

    Risk-Based Prioritization

  • 03

    Test-Driven Refactoring

  • 04

    Domain-Driven Decomposition

Incremental Modernization

Incremental Modernization

We pick small, high-value modules to refactor first. We use AI to propose micro-refactors like replacing deprecated APIs or removing dead code.

Risk-Based Prioritization

Risk-Based Prioritization

We let AI estimate the complexity and potential impact of changes (e.g., likelihood of introducing bugs), tackling low-risk, high-reward refactors first.

Test-Driven Refactoring

Test-Driven Refactoring

We ensure a solid baseline of tests, using AI to generate or augment unit tests around the refactored code to prevent regressions.

Domain-Driven Decomposition

Domain-Driven Decomposition

We leverage AI to identify bounded contexts and suggest modular boundaries, gradually extracting self-contained modules (Strangler Fig pattern).

Powering Global Growth with Artificial Intelligence

We pair AI with deep engineering expertise to modernize legacy estates, streamline delivery, and unlock new value.


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development centers

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offices globally

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IT professionals

Success Stories

From decoding legacy systems to strengthening production environments,
Ciklum unlocks true enterprise modernization with AI-driven precision.

Engineering the World’s Largest Food Delivery Platform

Engineering the World’s Largest Food Delivery Platform

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Transforming the Mortgage Transfer Process for Santander

Transforming the Mortgage Transfer Process for Santander

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Optimizing and Future-Proofing Payment Infrastructure for Betsson

Optimizing and Future-Proofing Payment Infrastructure for Betsson

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