kCode by Inter-K is your modernization map. We use advanced AI to automatically analyze millions of legacy lines of COBOL, Java, .NET, and more — turning decades of complexity into a clear, actionable blueprint with 75% cost savings.
Four compounding forces push organizations into a state of paralysis — each making the next step harder.
Cited by CIOs as a primary blocker (McKinsey, 2022). It's nearly impossible to understand system functionality without extreme manual effort — migration planning cannot begin.
Undocumented field-level logic woven across systems creates a "spider-web" effect, significantly increasing the probability of catastrophic migration failure.
Experts in COBOL, C#, Java, and JavaScript are retiring. Replacements are scarce, leaving enterprises with critical systems and no one capable of maintaining them.
A lack of rollback options or automated validation prevents confident execution. Teams default to "maintaining status quo" rather than risking a broken modernization plan.
The kCode Service is your modernization map. We use advanced AI to automatically analyze your millions of legacy lines of code, turning decades of complexity into a clear, actionable blueprint for your modernization project.
We take the guesswork out so you can move forward with speed and certainty. Our kCode Service leverages the kCode AI engine to automate legacy code analysis for migration inventory — supporting COBOL, Java, .NET, Node.js, and virtually any legacy language your enterprise has accumulated.
From analysis to action: kCode extracts consistent system insights in structured formats, optimized for easy consumption by downstream migration tools and AI agents — delivering documentation that was previously impossible to produce at this speed and cost.
Automatically transforms your codebase into a living, up-to-date document — logic and specs always in sync.
Cut documentation time by over 50% vs. manual — unblocking stalled projects immediately.
Extract system insights in structured JSON, optimized for downstream migration tools and AI agents.
Configure dynamic output formats to meet every client's unique architectural standards and business needs.
See exactly what changes when kCode becomes part of your modernization strategy.
A secure, multi-layered AI ecosystem for automated legacy logic reconstruction — from input to structured output.
Provide your source code (COBOL, Java, .NET, Node.js, and more...), existing documents (PDF, Word, Excel, Images), and optionally your output template. kCode works with what already exists — no changes required to your system.
kCode AI Engine cross-references source code, documents, and context. The AI Agent Fleet (Devs, QAC, PO/BA agents) applies predefined rules and tasks, automatically building structured artifacts. One-time setup, then fast, consistent, and scalable analysis.
All documents generated in 1–3 weeks depending on system size. Delivered via web dashboard, Excel reports, PDF documents, or Markdown/JSON for further use — ready for developers, managers, auditors, or customers.
Strategic assets ready to support modernization, onboarding, audits, or automation — generated in 1–3 weeks.
Structured system requirement specs extracted from legacy code. Covers all functional and non-functional requirements, aligned to your preferred template.
Visualized modules, job flows, and screen interactions. Complete picture of your system architecture — modules, services, databases, and all interaction flows mapped end-to-end.
Table of inter-module dependencies, data exchanges, and variable usage. Every internal and external dependency catalogued with full impact assessment.
kCode's proprietary System Complexity Index — a quantitative score for prioritization and scoping. Helps you identify which modules to modernize first based on complexity, risk, and effort.
Human-readable logic specification for each program, method, or job. Business rules, calculations, and decision logic translated from code into plain-language documentation.
JSON-based output optimized for API integration, low-code migration, and agent training pipelines. Machine-readable specs your dev team can use directly in modernization projects.
At the core of every kCode engagement is the Document Definition Layer — driving how documents are created with business-centric and technical-centric templates.
Top-level project structure and scope overview
Feature or sub-features split by business domain, not technical boundaries
User story format to clarify and set specifications for features
Business rules that the software implements and enforces
Business concepts and entities — purely conceptual, business-centric design
Process flow of the system to deliver and implement user stories
Separated by source code repository boundary (front-end, back-end, etc.)
Technical function living within bounded context, separated by system boundary
UI Screen or Dialog specification of the project
Reusable UI components found in the codebase
Database tables that the system directly interacts with — schemas and relationships
HTTP API specification — endpoints, parameters, request/response structures
kCode serves three distinct groups — each with different needs, all unblocked by the same platform.
Three pillars that set kCode apart from every other approach to legacy documentation.
Two deployment architectures — choose based on your infrastructure requirements and data sensitivity.
Best for rapid engagements and low infrastructure overhead
Best for strict data isolation and regulatory compliance
Outbound access to LLMs (Anthropic, Gemini, OpenAI, Qwen, Kimi, or GLM). Environment must support Kubernetes for containerized deployment.
Four structured phases define every kCode engagement — from kickoff to final delivery.
These baseline requirements ensure kCode can deliver maximum accuracy and speed from day one.
Click any story to read the full case study — from automotive giants to government agencies.
30 years of development history — 664 SRS documents generated with 100% accuracy before a single line of new code was written.
Cross-platform inventory system mapped end-to-end via AI Agent Fleet — greenlighting full-scale OutSystems migration.
Visual AI reconstructed a complete 1990s government system from screenshots alone — 90% time and cost saved vs. manual.
Post-acquisition codebase mapped and split in 2 weeks — enabling timely board approval for migration strategy.
AngularJS & .NET critical app documented in 4 weeks with self-configurable templates and zero data exposure.
See why leading APAC enterprises choose kCode over manual processes or generic AI tools.
| Capability | Manual Process | Generic AI Tools | kCode by Inter-K |
|---|---|---|---|
| Time to Complete | 12–18 months | 3–6 months | 3–4 weeks |
| Cost vs. Manual | 100% baseline | ~40% savings | 60–75% savings |
| Zero-Source Code Support | Not possible | Not possible | ✓ Screenshots only |
| COBOL, Java, .NET & More... | Expert required | Limited | ✓ Any legacy language |
| Human-in-the-Loop QA | ✓ (very slow) | ✗ Automated only | ✓ Expert validated |
| SCI Complexity Scoring | ✗ | ✗ | ✓ Proprietary metric |
| On-Premise Deployment | N/A | ✗ Cloud only | ✓ Client hosted option |
| Data Isolation (Zero Exposure) | ✓ | ✗ Data sent to cloud | ✓ 100% isolated |
| Output Formats | Word, PDF | Markdown, JSON | PDF · Word · Excel · JSON · Web |
Structured to ensure no surprises — from early exploration to large-scale migration.
Inter-K standard SRS and BRD templates. Rapid delivery with minimal overhead. Fixed service fee.
Detailed SRS analysis tailored to your formats. Artifact identification and deep dive into specific assets. Bespoke pricing logic.
Additional features from kCode base. Pay based on software customization pricing. Logic-based pricing optimized for client use cases.
Start with a free basic analysis. No commitment — see exactly what kCode will deliver before you sign anything.