Everything a full migration engagement delivers—parsing, dependency analysis, complexity scoring, conversion, verification, documentation—all in a platform your dev team operates directly.
A streamlined process designed for enterprise-scale migrations.
Upload your COBOL codebase. Deep parsing with preprocessing, copybook resolution, and full syntax tree construction.
Build dependency graphs, call-chain analysis, complexity scoring, and risk assessment across your entire system.
Agentic AI converts to your target language. Automated verification proves functional equivalence with the original.
Convert → Verify → Fix → Repeat. The AI iterates until 100% of functions pass equivalence tests.
Drag the slider to compare legacy COBOL with modernized Python.
from decimal import Decimal
from dataclasses import dataclass
@dataclass
class InterestCalculator:
principal: Decimal
rate: Decimal
years: int
def calculate_interest(self) -> Decimal:
"""Calculate simple interest."""
interest = self.principal * self.rate * self.years
return interest.quantize(Decimal("0.01"))
def display_result(self) -> None:
print(f"INTEREST: {self.calculate_interest()}") IDENTIFICATION DIVISION.
PROGRAM-ID. CALC-INTEREST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-PRINCIPAL PIC 9(9)V99.
01 WS-RATE PIC 9(2)V9(4).
01 WS-YEARS PIC 9(2).
01 WS-INTEREST PIC 9(9)V99.
PROCEDURE DIVISION.
COMPUTE WS-INTEREST =
WS-PRINCIPAL * WS-RATE * WS-YEARS.
DISPLAY "INTEREST: " WS-INTEREST.
STOP RUN.Everything a migration consulting firm delivers—parsing, analysis, conversion, verification, documentation—all AI-powered.
Complete preprocessing, copybook resolution, nested COPY handling, and full syntax tree construction for any COBOL dialect.
Automatic call-chain analysis, program interdependencies, and visualization of your entire system architecture.
Risk assessment and migration difficulty estimation for every module, helping you prioritize and plan.
AI-powered transformation to Python, Java, TypeScript, C#, Go, or any modern language your team prefers.
Proving functional equivalence between source and target through generated test suites and behavioral analysis.
Comprehensive coverage analysis identifies corner cases. The AI handles them—or flags them for human review.
Documenting and preserving critical business logic, making tribal knowledge explicit and maintainable.
VSAM, DB2, IMS, sequential files → modern databases (PostgreSQL, MySQL, MongoDB, etc.) with zero data loss.
Parallel-run strategies, phased migration plans, and rollback procedures for safe production deployment.
Complete documentation, stakeholder reports, and compliance artifacts for governance and audit.
Convert → Verify → Fix → Repeat. The AI keeps iterating until every function is verified and passing.
Auto-generated test suites from observed behavior, not outdated specs. 100% coverage is the baseline, not the goal.
Skip the lengthy consulting engagements and extended timelines. Your dev team runs the migration. AI does the heavy lifting.