AI × Legacy Modernization
Smart Rewrite — next-generation modernization powered by the speed of AI and explainable quality.
We make complex legacy systems fully transparent through structured-data technology. A proprietary verification process eliminates AI hallucinations to guarantee a safe, reliable migration — and our future-ready platform lets AI keep improving your business after launch.
Auto-generated design accuracy
≥ 0 %
Effort reduction
0 %
Features
1 POINT 01
We combine the speed of generative AI with quality beyond human review. Our pipeline separates Generation and Analysis into mutually monitored streams and adds an independent Verifier that objectively scores every output. The result: hallucinations are removed, missing business logic and misread context are auto-detected and corrected, and you get a fact-grounded, safe migration.
2 POINT 02
We extract structure and meaning from legacy code using Abstract Syntax Trees (AST) and Intermediate Representation (IR), then auto-generate the current detailed design — CRUD diagrams, data dictionaries, and more. Tacit business rules and edge cases that previously lived only in one engineer's head become visible, breaking the black-box and key-person dependency for good.
3 POINT 03
After modernization you keep enjoying AI: code and test generation, early bug detection, and other AI assists are natively integrated into your maintenance workflow. The maintenance overhead that consumed most of your IT budget shrinks dramatically, freeing resources for new business and DX investment — turning IT from a cost center into a strategic asset and lifting overall profitability.
Process
End-to-end process
Run design → conversion → test on representative features and report a quality score.
Inventory assets and dependencies, estimate automation rate, and define scope.
Define the target state (architecture, framework) and dictionary policy.
Reuse the dictionary and templates as shared assets across the organization.
Supported languages
COBOL, RPG, PL/1, IDL II, VB, .NET, Java, Delphi, C, C# — and we adapt to whichever target language you need.
Why NTQ
Quality-assured Smart Rewrite × top Vietnamese talent = "Co-creation offshore"
Japanese consultants at NTQ Consulting Japan handle the upstream work; development is delivered by our Vietnamese teams — not as cheap labor but as a co-creation model with elite engineers fluent in Agile, DevOps, and generative AI. You get deep expertise and the latest technology while cutting operating and development costs by up to ~50%.
A seamless co-creation model
Owns upstream work, requirements, project management, and quality tuned to Japanese business practice.
Fast, high-quality implementation powered by Agile, DevOps, and generative AI.
Case Study
Major food wholesaler
Source language
COBOL
Target language
C#
Migration technology
Smart Rewrite powered by generative AI
COBOL source
400,000 steps
Duration
16 months
Effort
230 person-months
(assessment → data migration)
Problem
Is a system you're "afraid to touch" stealing your company's future?
Many organizations face severe legacy-system risk today. The so-called "2025 cliff" is no longer a forecast — it is a reality companies are living through. Ignoring it is said to cost tens of billions of yen per year. Why are aging systems such a strong DX inhibitor? Behind every mainframe shutdown is the heavy reality that ~80% of IT budget is locked up in maintenance.
Worse still, there is no effective response in place for the IT-talent shortage. Veteran engineers retire, the COBOL talent pool keeps shrinking, and many organizations have hit a maintenance ceiling. Without solving system black-boxing — where specs are scattered and only one person understands the code — drawing the next business strategy is impossible.
While they cling to legacy, companies cannot enjoy modern AI or cloud. Yet, faced with a giant core-system replacement, many freeze for fear of a big-bang failure that halts the business.
Soaring maintenance cost squeezes strategic investment. Long-term dependency keeps you locked in with a single vendor.
COBOL engineers are gone, specs are missing, and the system is a black box that breaks when you touch it.
Data silos block AI integration, the test environment is incomplete, and slow releases mean you can't keep up with business speed.
Limitations
Plain re-host and legacy auto-conversion tools have hidden traps
Rushing modernization too often pushes the real problem into the future.
Lifting the system as-is leaves internal logic black-boxed. Maintenance and operating cost stay unsolved at the root.
Auto-conversion is opaque and ungrounded; mechanical rewrites without business-logic understanding leave quality in doubt.
Output that looks 60–80% complete often contains hallucinations and broken logic — and the cost of full human review wipes out the time savings.
Contact
We never recommend a big-bang migration. We build a reliable plan through asset inventory and a focused PoC.
FAQ
Rule-based COBOL→Java tools just substitute syntax, leaving you with "unreadable Java" full of redundant logic. Plain generative-AI approaches add a different problem: hallucinated code that looks plausible but is wrong. NTQ's Smart Rewrite uses proprietary AST and IR technology to structure both the facts and the meaning of the code. From that we first auto-generate an accurate detailed design, then translate to a modern language using that design as the source of truth. Going through the design layer eliminates semantic bugs and produces high-quality, explainable code.
Re-hosting (mainframe emulator, etc.) is a quick straight conversion — short timeline, low cost — but it does not solve the black-box problem (emulators tend to be a stop-gap). Smart Rewrite preserves the intent of the original code while rebuilding on a modern architecture, making future cloud migration, API exposure, and ERP-to-legacy integration far easier.
Yes. Java and C# are the most common targets from COBOL, but we convert to whichever modern language fits your future architecture and help you open up the mainframe.
Traditional testing relied on huge manual diffs between old and new. NTQ's flow generates a "reference detailed design" from the old code and a "validation spec" from the new code, then has AI semantically diff them. Any missing function triggers an automatic detect-and-fix loop — a quality gate that drives migration risk close to zero.
Cost and timeline depend on system size, but our hybrid offshore model — generative AI plus top Vietnamese engineers — has shortened migrations by ~30–40% and cut cost by up to 50% versus manual rewrites. We recommend starting small with a PoC as the first concrete step away from the mainframe.
Yes — many large enterprises, including finance migrations under strict requirements and logistics migrations where downtime is not an option. We can share migration plan templates and case packs, so feel free to reach out if you're comparing migration vendors.
