3X CODE CONVERSION

Convert Legacy Code to Modern Cloud in Hours.

Automated legacy code conversion for enterprise cloud migrations. Thousands of SQL scripts, stored procedures, and ETL jobs converted to target platform-native code with built-in validation, not months of manual line-by-line rewriting. 3X Code Conversion delivers production-ready output in hours, with every object parsed, scored, converted, and tested.

Conversion Run — Teradata → Azure Synapse · 1,247 scripts
Code Ingestion & ParsingComplete
1,247 objects · 612 SQL queries · 389 views · 180 BTEQ scripts · 66 FastLoad jobs
Complexity AnalysisComplete
Scoring & classification across all objects
Agentic Code ConversionComplete
Translating Teradata SQL → Snowflake SQL...
Validation & TestingComplete
Automated regression testing & quality reports
1,000+Scripts converted per run
WeeksNot months of manual conversion
8 - 12Weeks vs 6 - 10 months
5+Target platforms supported
VS
WITHOUT 3X CODE CONVERSION
SQL Script Conversion12 - 14 months
Stored Procedure Refactoring6 - 8 months
ETL Job Migration8 - 10 months
Testing & Validation4 - 6 months
Code Quality StandardisationManual, inconsistent
Documentation and LineageIncomplete or Missing
Developer GuidanceTribal Knowledge Only
WITH 3X CODE CONVERSION
SQL Script ConversionMins to convert, hrs to finalize
Stored Procedure RefactoringMins to convert, hrs to review
ETL Job MigrationHrs to convert, days to validate
Testing & ValidationAutomated, hrs to review results
Code Quality StandardisationBuilt-in, enforced at conversion
Documentation and LineageAuto-generated at ingestion
Developer GuidanceAI-generated with full context

Legacy code satisfies neither your cloud timeline nor your budget.

Every stalled migration traces back to the same bottlenecks. Manual conversion, missing documentation, inconsistent quality, and platform-specific syntax that no generic tool can handle. 3X Code Conversion eliminates these blockers at scale.

Manual Conversion That Doesn't Scale

Thousands of SQL scripts, stored procedures, and ETL jobs requiring heavy manual work, line by line, object by object. Entire teams consumed for 12 to 18 months with effort that scales linearly because there is no reusable pattern extraction.

Proprietary Syntax With No Cloud Equivalent

Legacy platforms use proprietary SQL dialects, control flow constructs, and data loading utilities with no direct mapping to modern cloud platforms. Each syntax gap requires heavy manual interpretation, rewriting, and testing by engineers who understand both source and target.

Business Logic Buried in Undocumented Code

Critical business rules, exception handling, and conditional transformations buried inside stored procedures and ETL jobs written over 10 to 15 years. No documentation. The engineers who built them have moved on. Converting syntax is mechanical. Preserving business intent requires heavy manual analysis.

Inconsistent Quality Across Conversion Teams

Multiple engineers converting code independently, each applying different naming conventions, formatting standards, and optimization patterns. The result is a converted codebase with no consistency, no enforced platform best practices, and significant technical debt before the first deployment.

No Validation or Regression Testing Framework

Most manual conversions skip systematic testing because there is no framework to validate output at scale. Errors surface in production as broken logic, incorrect data, and costly rollbacks that erode stakeholder confidence in the migration.

Platform Expertise Scarce and Spread Too Thin

Every source-to-target combination demands engineers who understand both the legacy syntax and the target platform architecture. That expertise is scarce, expensive, and impossible to scale when heavy manual conversion work consumes the same people who should be making design decisions.

Intelligent Code Conversion. Not Find-and-Replace.

Intelligent Code Conversion. Not Find-and-Replace. AI-powered automated code conversion that understands legacy logic, resolves dependencies, and generates platform-native code with built-in quality gates.

Deep Code Understanding

AI-Powered Semantic Analysis

Parses legacy SQL, stored procedures, and ETL logic at the semantic level, not syntax level. Resolves implicit dependencies, embedded business rules, platform-specific constructs, and undocumented control flows that pattern-matching tools and generic LLMs miss entirely. Every object is fully understood before automated conversion begins.

Complexity Scoring & Classification

Risk-Based Prioritization Before Conversion.

Automatically scores every legacy code object by structural complexity, dependency depth, cross-system references, and conversion risk. Classifies objects into conversion tiers so teams know exactly which objects convert cleanly, which need human review, and which carry downstream migration risk. Eliminates guesswork in sprint planning.

Agentic Code Conversion

Goal-Aware, Multi-Pass Conversion Engine.

Goes beyond line-by-line SQL translation. The agentic conversion engine understands the intent behind legacy logic and reconstructs it using target platform-native patterns, optimized joins, and modern SQL constructs. Each object goes through iterative validation passes until output meets defined quality gates. No hallucinated table names. No missing columns.

Automated Refactoring

Platform-Native Optimization, Not Literal Translation.

Refactors converted code to eliminate legacy anti-patterns, reduce redundant logic, and apply target platform best practices for Snowflake, Databricks, Synapse, or Fabric. Output is production-ready code optimized for the new platform, not a literal copy that compiles but runs inefficiently with legacy performance patterns.

Automated Testing & Validation

Built-In Data and Logic Validation at Every Stage.

Generates and executes test cases automatically for every converted object. Validates row counts, column mappings, data type conversions, null handling, join logic, and business rule equivalence between source and target. Issues are flagged with root cause before deployment, not discovered in production after go-live.

Developer Action Items

Clear, Actionable Guidance for Every Flagged Object.

Every object requiring human attention comes with specific, prioritized action items: what failed validation, why, the exact line in converted code, and what the developer needs to resolve. No vague warnings or generic error logs. Engineers spend time fixing known issues, not reverse engineering conversion output.

From legacy codebase to production-ready output.

A three-stage intelligent pipeline that ingests, converts, and validates your entire legacy codebase automatically.

Convert Legacy Scripts to Modern Data Platforms — 1,000+ Objects in Hours
YOUR LEGACY CODEBASE
3X CODE CONVERSION
DELIVERABLES
SQL Scripts
Stored Procedures
ETL Scripts
BTEQ & Macros
Legacy Codebases
  • Cross Platform
  • Complex Logic
  • 1,000+ Scripts
  • Undocumented Code
Deep Code Understanding
Complexity Scoring
Agentic Code Conversion
Automated Refactoring
In-Built Validation
Developer Action Items
Fully Converted Production-Ready Code
Partially Converted Code with Clear Action Items
Conversion Validation Reports
Standardised Formatting & Comments
Migration Summary & Effort Insights
AI-Assisted Code Review

See exactly what you get.

Every conversion run produces structured, auditable deliverables. Here's a live preview of what your team receives.

  • Conversion Summary
  • Complexity Scorecard
  • Validation Report
  • Developer Actions
CONVERSION OVERVIEW
1,247Total Objects
1,089Fully Converted
158Partial / Action Needed
CONVERSION RATE
87.3%
Fully Automated Conversion Rate
CONVERSION BY OBJECT TYPE
SQL Scripts94% converted
Stored Procedures82% converted
ETL Jobs79% converted
BTEQ Macros68% converted
Views & Functions96% converted

From any legacy platform. To any modern cloud.

3X Code Conversion handles cross-platform migrations natively. Source and target — covered.

Teradata

Teradata

BTEQ, SQL, stored procs

✓ SourceBTEQSQL
Oracle

Oracle

PL/SQL, packages, triggers

✓ SourcePL/SQL
Netezza

Netezza

SQL, stored procs, NZPLSQL

✓ SourceNZPLSQL
SQL Server

SQL Server

T-SQL, SSIS, stored procs

✓ SourceT-SQL
Snowflake

Snowflake

Snowflake SQL, Snowpipe

✓ TargetCloud DW
Databricks

Databricks

Spark SQL, Delta Lake

✓ TargetLakehouse
BigQuery

BigQuery

Standard SQL, BigQuery ML

✓ TargetCloud DW
Microsoft Fabric

Microsoft Fabric

Synapse, Data Factory

✓ TargetFabric

Every legacy platform. One conversion engine.

3X Code Conversion supports the most in-demand enterprise migration paths. Same AI-powered engine, same quality gates, adapted for each source-to-target platform pair.

Production-ready code. From day one.

Everything your team needs to convert, validate, and deploy, delivered automatically. Less rework cycles. Less manual cleanup.

01

Hours, Not Months

Automated code conversion for 1,000+ legacy objects delivered in hours, not the 12-18 months of manual line-by-line SQL translation that stalls enterprise cloud migrations and burns through project budgets before the first object reaches production.

02

Production-Ready Output

Converted code follows target platform best practices for Snowflake, Databricks, Synapse, and Fabric with optimized query patterns, proper formatting, and platform-native constructs. Ready for deployment and performance testing, not another round of manual refactoring.

03

Built-In Quality Assurance

Automated validation and regression testing at every conversion stage ensures business logic integrity is preserved across platforms. Row counts, data types, null handling, and join logic verified before any converted object moves forward to deployment.

04

Actionable Developer Guidance

Every partially converted or flagged object includes clear, specific developer action items with full context: what failed, why, where in the code, and exactly what needs to be resolved. Engineers fix known issues in minutes, not spend days investigating conversion output.

See Code Conversion in Action

Get a personalised walkthrough tailored to your legacy code conversion and cloud migration requirements.

Let's talk scale.

Our team of engineering experts and AI architects is ready to help you accelerate your data modernization journey.

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