AI-Powered Tool for Automated Migration from Softacom

Name: AI-Powered Tool for Automated Migration from Softacom
Brand: Softacom

20

Years of Experience in Software Development

50%

Automated Process

3x

Faster Migration

99.9%

Migration Accuracy

AI-powered migration based on 20+ years of Delphi & .NET expertise

Our AI-powered migration tool is built for real-world enterprise use cases. It performs a deep analysis of your app’s architecture, allowing for faster and safer migration.

Complete codebase inventory

Component structure mapping

Unit classification and dependency graph

Migration effort estimation

Intelligent code transformation

We’ll review your legacy codebase and send you an AI-generated migration report within 48h.

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With Our AI-Powered Migration Tool, You Get

3x Faster Migration

AI automates code transformation, making migration up to 3x faster.

High Accuracy

The AI-based migration tool retains up to 90% of the code structure and logic, minimizing errors and manual fixes.

Secure & Compliant

Your code stays within your infrastructure, ensuring full data protection.

Cost-Efficient

AI automation reduces manual effort, lowering migration costs.

Seamless Integration

The AI migration tool easily connects your app with modern databases, APIs, cloud services, and DevOps tools.

Future-Proofed Technology Stack

AI converts legacy applications into modern Delphi and C#/.NET solutions.

Comprehensive Approach

Softacom combines AI-driven software with manual migration. It is executed by experts with over 20 years of experience in software migration and modernization.

AI Built for Enterprise Migration

Trained on 20+ years of legacy code, our AI-powered tool expertly handles Delphi and .NET migrations precisely.

Get a Free AI-Based
Migration Report

Compatibility with Programming Languages

Languages

Delphi (Object Pascal)
C#
T-SQL
VB
PowerShell
С++
SQL
Python
JavaScript
Typescript
Swift
Objective-C
Java
Kotlin

Step-by-Step Migration Process with Softacom AI-Driven Tool

01 step

Define

Defining the source code paths in our tool. The tool scans these paths, identifies relevant project files, and filters out unnecessary ones.

02 step

Scan

AI scans your selected projects, identifying structures, counting files and forms, categorizing unit types, and mapping dependencies.

03 step

Translate

The AI engine translates the legacy code into the new selected language, IDE, or framework. It speeds up the conversion by automatically resolving common migration issues.

04 step

Refine

To align with your business needs, our experts refine the code, optimize integrations, and enhance its performance.

05 step

Deploy

We finalize the project and deploy it in your modern environment.

“Softacom’s Tool processed hundreds of thousands of lines and flagged 95% of legacy patterns for automated migration. It saved us months of refactoring and dramatically reduced the risk of human error.”

CTO, Global ERP Platform Provider

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How Does Our AI-Powered Migration Tool Work?

The Softacom AI migration tool is verified by engineers and trusted by clients.

Our AI-powered engine uses:

Deep Learning
Natural Language Processing (NLP)
Predictive Analytics
Computer Vision

Deep Learning

Deep Learning analyzes code structure and recognizes complex Delphi patterns that standard tools miss.

Custom attributes and RTTI enable dynamic UI control binding, which static tools often overlook. DeepML detects the correlation between TBindableField attributes and runtime loops over RTTI properties, ensuring accurate data linkage.

Delphi Code

type

TBindableField = class(TCustomAttribute)

private

FFieldName: string;

public

constructor Create(const FieldName: string);

property FieldName: string read FFieldName;

end;

TUserModel = class

public

[TBindableField('UserName')]

FName: string;

end;

procedure BindModelToUI(AModel: TObject; AForm: TForm);

var

Ctx: TRttiContext;

Field: TRttiField;

Attr: TCustomAttribute;

Component: TComponent;

begin

Ctx := TRttiContext.Create;

try

for Field in Ctx.GetType(AModel.ClassType).GetFields do

for Attr in Field.GetAttributes do

if Attr is TBindableField then

begin

Component := AForm.FindComponent(TBindableField(Attr).FieldName);

if Component is TEdit then

TEdit(Component).Text := Field.GetValue(AModel).ToString;

// Dynamic binding

end;

finally

Ctx.Free;

end;

Natural Language Processing (NLP)

Natural Language Processing (NLP) processes comments and variable names to preserve business logic when migrating to .NET.

This is how NLP identifies Policy 2021-5A as a business rule for Gold customers, maps CustomerType to customerType, retains the Gold check, and adds a policy reference as a comment in C# for traceability. This ensures that even brief comments preserve intent throughout the migration.

Before

After

// Apply 10% discount for "Gold" customers (Policy 2021-5A)

if CustomerType = 'Gold' then

Total := Total * 0.9

// NLP detects "Gold" and "Policy 2021-5A" to retain discount logic

if (customerType == "Gold")

total *= 0.9m; // Policy 2021-5A: 10% Gold customer discount

Predictive Analytics

Predictive Analytics identifies high-risk areas, detecting 500+ potential errors per 1 million lines of code, which saves up to $75,000.

Predictive analysis detects null risks (sourceAccount/targetAccount) and race conditions (SaveToDatabase()), estimating ~12 null refs and ~8 race conditions per 10K lines. Fixing costs: $50/error pre-release, $1,500/error post-production.

C#

public class TransactionProcessor

{

private Account _sourceAccount;

private Account _targetAccount;

public void Transfer(decimal amount)

{

// No null-check for accounts (high-risk pattern)

_sourceAccount.Balance -= amount;

_targetAccount.Balance += amount;

// No thread-safety for concurrent transactions

SaveToDatabase();

}

private void SaveToDatabase()

{

// Logic of saving to the DB

}

Computer Vision

Computer Vision automatically converts VCL Delphi forms into modern FireMonkey (FMX) Delphi forms or .NET forms like WinForms and WPF.

Before

After (WinForm)

After (FireMonkey)

object LoginForm: TLoginForm

object lblUsername: TLabel

Caption = 'Username:'

Left = 24

Top = 32

Font.Color = clNavy

end

object edtUsername: TEdit

Left = 24

Top = 56

Width = 200

end

object btnLogin: TButton

Caption = 'Login'

Left = 24

Top = 100

Width = 75

OnClick = btnLoginClick

end

// Auto-generated WinForms code

public partial class LoginForm : Form

{

private Label lblUsername = new Label();

private TextBox edtUsername = new TextBox();

private Button btnLogin = new Button();

public LoginForm()

{

// Label

lblUsername.Text = "Username:";

lblUsername.Location = new Point(24, 32);

lblUsername.ForeColor = Color.Navy;

Controls.Add(lblUsername);

// Textbox

edtUsername.Location = new Point(24, 56);

edtUsername.Size = new Size(200, 20);

Controls.Add(edtUsername);

// Button

btnLogin.Text = "Login";

btnLogin.Location = new Point(24, 100);

btnLogin.Size = new Size(75, 23);

btnLogin.Click += btnLogin_Click; // Event mapped

Controls.Add(btnLogin);

}

private void btnLogin_Click(object sender, EventArgs e)

{

// Logic migrated from Delphi's btnLoginClick

}

object LoginForm: TLoginForm

object lblUsername: TLabel

Text = 'Username:'

Position.X = 24.000000000000000000

Position.Y = 32.000000000000000000

TextSettings.FontColor = claNavy

end

object edtUsername: TEdit

Position.X = 24.000000000000000000

Position.Y = 56.000000000000000000

Size.Width = 200.000000000000000000

end

object btnLogin: TButton

Text = 'Login'

Position.X = 24.000000000000000000

Position.Y = 100.000000000000000000

Size.Width = 75.000000000000000000

OnClick = btnLoginClick

end

Migration Timeline

Steps

100k lines of code

1M+ lines of code

01

Assessment and Planning

Analysis of the current system, code, and architecture
Estimating the complexity of migration
Defining business goals and KPIs

1-2 weeks

2 weeks

02

Creating a Proof of Concept (PoC)

Selection of the target platform and technologies
Analysis of the infrastructure requirements
Development of a Proof of Concept
Verification of migration feasibility and analysis of potential issues
Validation of architecture compliance with business requirements

2-4 weeks

4-6 weeks

03

Setting Up the Environment

Creation of a development environment
Back up existing data and code
Preparation of the database schema for the target platform

Up to 1 week

1 week

04

Automated and Manual Code Transformation

Using Softacom’s AI-powered tool for automated migration to analyze and convert code
Manual optimization and refactoring if needed
Ensuring compatibility with modern APIs and libraries

2-3 months

3-4 months

05

Testing and Debugging

Unit testing of individual modules
Integration testing
Production testing in a real environment

2-4 weeks

2-3 months

06

Optimization and Refinement

Performance improvements
Enhancements to UI, integrations, and logic

1-2 months

2-3 months

07

Deployment

Migrating the new system to the production environment
Minimizing downtime
Final testing before release

1-2 weeks

2 weeks

08

Maintenance and Support

Post-launch monitoring
Training for users and technical team
Long-term support and improvements

4-9 months

9-13 months

*The timeline depends on several factors, including the size of the software, team composition, project deadline, complexity of the original code structure, and technology compatibility.

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Explore Our AI Capabilities

Beyond intelligent migration, Softacom helps businesses unlock the full potential of AI. We build and deploy solutions that analyze images, videos, and data using deep learning, neural networks, and machine learning — across technologies like Python, C++, Java, Delphi, .NET, and more.

Learn more

Why Softacom?

50% Automated Process
Expertise in AI
Full Support of Legacy & Modern Framework
Strict Quality Assurance
Integration with Modern Frameworks
Guaranteed Results
15+ Years of Experience

Our solution automates over 50% of the migration process. Manually rewriting an enterprise-level application can take up to 5 years. But our automated approach reduces this to around 2 years. As a result, the migration is accelerated by up to 3x.

Backed by 20 years of software development experience, our team leverages AI-powered solutions for precise, reliable, and business-tailored migrations.

Seamless migration across legacy and modern platforms, with full support for a wide range of Delphi and .NET versions.

We ensure that each project undergoes a rigorous testing and validation process. Automated migration results in fewer than 1 defect per 1,000 lines of code. This helps us ensure 99.9% error-free migration results.

We support .NET Core, ASP.NET, Entity Framework, VCL, Xamarin, FireMonkey (FMX) and more.

We align migration with your business goals. Customer satisfaction is at the core of our approach.

With over 15 years in software modernization, we have successfully migrated 100+ projects of varying complexity, rewriting a total of over 40 million lines of code.

Softacom Accelerates Migration with AI-Powered Tool

How is migration using an AI tool better than traditional approaches?
01

AI tools help automate routine tasks. This reduces human error and helps preserve business logic more accurately. But AI doesn’t replace engineers, it supports them. Experts still handle complex decisions, verify results, and adapt the system to business needs.

Is it possible to partially migrate the system, leaving some modules unchanged?
02

Yes, our AI tool supports phased migration: you can update critical components first, gradually integrating them with your existing infrastructure without interrupting business processes.

How long does it take to complete a full migration from a legacy system using an AI tool?
03

The average time is from 4 to 13 months. But it will depend on the size of the software, team composition, project deadline, complexity of the original code structure, and technology compatibility.

How does the AI tool help optimize code and architecture during migration?
04

It analyzes dependencies, identifies duplication, suggests refactoring, and automatically updates the structure, so that the new system is not only modern but also efficient.