AI-Native Legacy Modernization

Modernize legacy
without losing
business truth.

AdeptRecode.ai transforms legacy artifacts—including documents, source code, user manuals, and application screens—into validated functional and technical insights, enabling the generation of target architectures, comprehensive documentation, and maintainable modern application code.

Start a Free PoC → See how it works
70%
of global transactions still run on COBOL - maintained by engineers mostly over 55
Rocket Software, 2025
75%
of IT budgets consumed by legacy maintenance, leaving little room for new development
Industry research, 2025
60%+
of large-scale rewrites fail or overrun - almost always because requirements were wrong from the start
Srinsoft, 2026
80%
reduction in migration time with AdeptRecode.ai vs manual rewrite programmes
AdeptRecode.ai data
Pilot outcomes

Results from the field,
not from a slide deck.

3 wks
Discovery to approved BRD
A 12-year-old .NET claims processing system — 847 modules — fully documented, business rules extracted, and BRD signed off in three weeks. Previously estimated at 6 months.
Financial services pilot
100%
Test coverage from day one
Every generated module shipped with Playwright E2E tests, unit scaffolding, and security test cases — all derived from the approved BRD, not written against the code after the fact.
Insurance platform migration
Zero
External data exposure
All analysis, documentation, and code generation ran on client-controlled infrastructure. No source code, business rules, or customer data left the organisation's environment.
Government agency deployment
Business outcomes

What AdeptRecode.ai
delivers for your organisation.

Six outcomes that matter to CIOs, CTOs, and transformation leaders.

📉
Dramatically lower modernization risk
Requirements extracted from real systems — not assumed in workshops. Scope is grounded before a single line of code is written, eliminating the leading cause of programme failure.
60%+ of rewrites fail because of wrong requirements.
⚡
Faster time to modernized capability
Weeks to first working output. Five pipeline phases run simultaneously. Your engineers receive a reviewed, tested codebase they can deploy.
80% reduction in migration time vs traditional programmes.
🧠
Preserve institutional knowledge
COBOL developers are retiring. AdeptRecode.ai extracts and documents decades of undocumented regulatory logic as a first-class deliverable — before it walks out the door.
70% of global transactions still run on COBOL.
🔐
Governance your auditors will trust
Human approval at every critical gate. Every generated artefact traced to its approved requirement. DORA, Basel IV, and HIPAA compliance built into the process from day one.
Chain of custody from source artefact to deployed code.
🏗
Code your engineering teams can own
Generated against your organisation's own architecture standards and component library — code your architects defined, your teams can navigate and maintain long-term.
Client-configured component library before generation begins.
🔒
Data sovereignty — no external exposure
Local LLM only. No source code, business rules, or customer data leaves your controlled infrastructure. Meets the privacy requirements of regulated industries without exception.
Zero external model-provider exposure in any pilot.
The strategic case

Enterprise modernization needs
governance + AI. Not just automation.

The AI is powerful.
Governance
makes it safe.
Direct AI migration Prompt → code No gates No traceability
❌
Why most rewrites fail
The team starts building before understanding the system. Requirements assumed. Business rules inferred. Result: 60%+ fail or overrun.
🔬
Extract before you build
Requirements extracted from real screens, real code, and real documents — reviewed by your domain experts before any build begins.
⏸
Human approval at every critical gate
Functional artefacts, architecture, and design approved at three mandatory gates. Code generation is constrained to what was approved.
🔒
Local LLM — your data stays yours
No source code, business rules, or customer data transmitted to any external model provider. Meets the privacy standards of regulated industries.
📋
Audit trail built in — not bolted on
Every decision traceable from deployed code back through the approved requirement to the original source artefact. DORA, Basel IV, HIPAA-ready.
Compliance and auditability

Regulatory confidence
built into the process.

AdeptRecode.ai doesn't produce compliance documentation after the fact. It generates audit-ready artefacts as part of the delivery — because governance is a first-class feature, not an afterthought.

📋
DORA readiness
Digital Operational Resilience Act requirements met through full traceability, documented business rules, and tested, auditable code. Incident response and change management artefacts generated as part of delivery.
Traceable from code to source artefact.
🏦
Basel IV compliance
Risk calculation logic, business rule provenance, and regulatory treatment documentation extracted during discovery and preserved through modernization. No undocumented logic survives the migration.
Business rule register classified by regulatory origin.
🏥
HIPAA alignment
Security patterns, data handling controls, and access governance baked into every generated module by the OWASP-aligned policy engine. Compliance posture inherited from the component library.
OWASP secure coding in every generated class.
🔗
Chain of custody
Every generated artefact linked back through the approved requirement to the original screen or document. The code lineage engine maintains bidirectional traceability — forward and backward query supported.
Forward + backward lineage query.
👥
Human decision audit log
Every decision made at a human approval gate is recorded with reviewer identity, timestamp, and reasoning. The governance audit log is a first-class deliverable — not reconstructed from version control history.
Reviewer identity + timestamp on every decision.
🔒
Data sovereignty
Local LLM deployment ensures no source code, business rules, customer data, or generated artefacts leave your controlled infrastructure. Meets the data residency requirements of regulated industries without exception or workaround.
Zero external model-provider exposure.
Business impact

The numbers that matter
to enterprise decision-makers.

Measured across pilot engagements. Validated against client baselines before engagement.

80%
Faster modernization
vs traditional SI timelines
70%
Less discovery effort
vs manual workshops
60%
Lower rework rate
through pre-build approval gates
4×
Faster onboarding
on generated codebase
Platform architecture

Eight specialised engines.
One governed modernization platform.

AdeptRecode.ai is not a wrapper around a single LLM. It is an orchestration platform with eight distinct engines - each with a bounded scope, communicating through the approved artefact store.

🔍
Static analysis engine
Discovery layer

Parses COBOL, .NET, VB6, Lotus Notes, C/C++ and Delphi. Builds AST, control flow graph, and data lineage map. Identifies dead code, hidden dependencies, and undocumented business rules.

AST parsingControl flow analysisData lineageCOBOL · .NET · VB6
🧠
Knowledge graph engine
Understanding layer

Builds a structured semantic graph linking screens, business rules, data entities, integrations, and source modules. Each node is attributed with origin artefact, lineage, and regulatory classification.

Semantic graphEntity relationshipsRule classificationNeo4j / compatible
📚
RAG pipeline
Retrieval layer

Retrieval-Augmented Generation over ingested artefacts - user manuals, help files, specifications, and training documents. Chunks, embeds, and indexes all documentation for the local LLM.

Chunking + embeddingSemantic retrievalpgvector / QdrantLocal embedding model
🤖
Agent orchestration layer
Coordination layer

Manages the multi-agent pipeline: discovery, documentation, architecture, code generation, and test generation agents. Each agent has bounded scope and communicates through the approved artefact store.

Multi-agent coordinationPhase-gated executionArtefact store handoffOllama / vLLM
📐
Policy engine
Governance layer

Enforces architecture standards, coding conventions, security requirements, and compliance rules at generation time. Non-conformant output is rejected, not passed downstream.

Architecture validationOWASP enforcementCompliance rule setOPA / custom engine
🔗
Code lineage engine
Traceability layer

Maintains a bidirectional link between every generated artefact and the chain of approved decisions that produced it. Supports forward and backward traceability queries.

Bidirectional lineageForward + backward queryAudit trail export
👥
Human review workflow
Approval layer

Structured review and sign-off interface for three mandatory approval gates. Presents generated artefacts alongside source evidence, inline annotations, corrections, and an audit log.

Three-gate approvalInline annotationReviewer audit logRBAC
⚙️
Deterministic code scaffolder
Generation layer

Generates application code, test suites, and infrastructure configuration from the client component library and approved BRD. Template-driven for structural decisions, local LLM for implementation detail.

Template-driven genComponent libraryParallel test gen.NET 8 · React · Java · Python
Why modernization fails

The "blind rewrite" failure mode
is still the norm.

"The code worked. Nobody knew why. We rewrote it. Now nothing works."

Most modernization efforts fail not because engineers can't write new code - but because they start writing before they understand what the old system actually does.

AdeptRecode.ai makes functional and technical understanding a primary outcome of modernization—not an optional step sacrificed to meet delivery deadlines.
The retiring engineer problem
The developers who built your core systems are leaving. They carry decades of undocumented logic - regulatory workarounds, fraud detection heuristics, edge cases nobody remembers writing. When they go, that knowledge disappears.
70%
The innovation tax
Every new initiative hits the same wall. Your teams spend half their time building translation layers between 1985 and 2025. APIs that should take days take months. The architecture stops you, not the ideas.
75%
Compliance without traceability
DORA, Basel IV, HIPAA - regulators want traceable, documented systems. But when your code has no documentation and no tests, every audit is a fire drill. You can't prove the system does what you think it does.
60%
The modernization pipeline

Five steps. One governed path.
No blind rewrites.

The complete modernization path - from legacy artefacts to deployed application - in a single governed pipeline. Each phase builds on approved outputs from the previous one.

Discovery pipeline — three parallel inputs feeding the unified knowledge base
Modernization flow diagram
Phase 01
Collect
Phase 02
Understand
Phase 03
Approve
Phase 04
Design
Phase 05
Generate
Artefact inputs
  • Legacy source code - COBOL, .NET, VB6, JAVA, FoxPro, Lotus Notes, C/C++, Delphi, PowerBuilder
  • User interface screens - scraped without source access
  • User manuals, help files, training documents
  • Existing specifications and architecture docs
What happens
  • All three discovery streams run simultaneously - UI, source, and documentation ingested in parallel
  • Local LLM processes artefacts inside controlled infrastructure - nothing leaves your environment
  • Screen flows, data models, integration points and business logic captured together
Output
  • Unified legacy knowledge base - structured, queryable, traceable to source artefacts
  • Dependency map across all ingested systems
  • Candidate business rule and workflow inventory - ready for expert review in Phase 03
Human-in-the-loop

Expert approval is a core product feature,
not an afterthought.

Modernization succeeds when hidden business knowledge is captured. AdeptRecode.ai keeps experts in the loop at the three moments that matter most.

Approval chain — who approves, what they approve, and the traceability backbone
Human-in-the-loop governance and approval diagram
Gate 1 - After Phase 02
Approve legacy functional artefacts
Before target design begins, application experts review and correct the extracted workflows, business rules and data flows. Errors corrected here cost nothing. Errors discovered after architecture generation cost weeks.
Gate 2 - After Phase 03
Approve technical understanding
Before the component architecture is generated, architects and technical leads validate the data model, integration contracts and dependency map. The target design is built on what was approved - not what was inferred.
Gate 3 - After Phase 04
Approve target design before code generation
The component architecture, API contracts, schema and deployment blueprint are reviewed and signed off before a single line of application code is generated. Code generation is constrained to what was approved. No surprises at delivery.
Why traceability matters

Every decision made at a human approval gate is linked back to the source artefacts that surfaced it. When an auditor asks why a business rule exists, AdeptRecode.ai can trace it - from the generated code, through the approved requirement, back to the original screen or document that captured it.

This isn't a log. It's a governed chain of custody for every business decision in the modernized system.

✓ Approve legacy functional artefacts before target design
✓ Approve technical understanding before architecture generation
✓ Approve target design before application code generation
✓ Keep traceability from every decision back to source artefacts
Target architecture

Built to match each organisation's
engineering standards.

The same modernization engine configured to generate code inside a client's existing framework - improving reuse and reducing long-term maintenance cost.

Input knowledge
What goes in
  • Legacy artefacts - code, screens, manuals, existing specifications
  • Approved functional and technical documentation from human review gates
  • Expert corrections and annotations applied during approval phases
  • Target stack choices - language, framework, BPM engine, deployment model
  • Organisation's existing component library, design system and API conventions
Generation rules
How it's constrained
  • Reference architecture templates - agreed per client before generation begins
  • Coding standards - SOLID, DRY, KISS, Clean Architecture, DDD as applicable
  • Security requirements - OWASP-aligned, SecDevOps pipeline embedded
  • API patterns - OpenAPI, REST, GraphQL conventions standardised across all modules
  • Testing guidelines - E2E, unit, integration and security test coverage strategy
Target outputs
What gets delivered
  • Component architecture - modular, independently deployable, peer-review ready
  • Target functional and technical design documents
  • Database schemas, data migration plan, API contracts
  • Full application code in your chosen stack
  • Test cases - E2E, unit, integration, security - generated in parallel with code
  • Production deployment - the full SDLC is in scope, including go-live
Quality posture
What's guaranteed
  • Maintainability - code that reads like code your team would have written
  • Traceability - every artefact linked to the approved requirement that drove it
  • Security - OWASP-aligned patterns in every module, SAST in every pipeline
  • Reviewability - generated code passes peer review from day one
  • Documentation coverage - BRD, TDD, API docs, data dictionary, runbooks
  • Deployment readiness - CI/CD, environment config, monitoring scaffolding included
Why AdeptRecode.ai

Different from asking AWS Transform, Google Mainframe Modernization,
and IBM watsonx Code Assistan to migrate your code.

Provider coding agents are powerful for developer productivity. AdeptRecode.ai is a governed modernization system - local execution, artefact-first understanding, approval gates and deterministic generation inside approved frameworks.

✗Direct provider migration - Prompt → generated code
✗Legacy code and documents may need to be sent to external provider environments unless separately controlled
✗Output depends heavily on prompts, model behaviour and session context - repeatability varies
✗Often starts from code conversion before fully documenting workflows, business rules and expert knowledge
✗Architecture and coding style may drift from organisation frameworks unless manually enforced every time
✗Review usually happens after code is produced - making corrections costlier
✓AdeptRecode.ai - Artefacts → approved design → generated app
✓Uses local LLMs - source code, documents and generated artefacts stay inside controlled infrastructure
✓Generation constrained by predefined frameworks, templates, standards and target architecture rules
✓Builds functional and technical understanding from documents, code, manuals and screens first
✓Customised to your organisation's existing framework - reuse, maintainability and standardisation
✓Application experts approve artefacts and target design before full code generation begins
Full SDLC coverage

From legacy artefact to production.
AdeptRecode.ai covers the whole journey.

Most modernization tools stop at code generation. AdeptRecode.ai covers the complete software development lifecycle - including deployment into production.

01
Discovery
UI scraping, source parsing, document ingestion - simultaneous
02
Requirements
BRD, functional spec, business rule register - auto-generated then human-approved
03
Architecture
Component design, API contracts, schema, BPM engine - after expert sign-off
04
Development
Code is generated from deterministic scaffolding, predefined templates, component libraries, and architecture recipes agreed with your team before generation begins.
05
Testing
E2E, unit, integration and security tests generated in parallel with code
06
Security
OWASP-aligned patterns, SAST, SCA and SecDevOps pipeline - built in from day one
07
Deployment
CI/CD pipeline, container configs, environment strategy, monitoring - production-ready
08
Documentation
API docs, data dictionaries, architecture diagrams, audit trail, compliance package
Component library approach

Before we generate one line,
we define every pattern you'll use.

"The client's framework shouldn't adapt to the tool. The tool should adapt to the client's framework."

Before code generation begins, AdeptRecode.ai works with your architects to assemble a client-specific component library - the reusable building blocks from which every generated module is constructed. Naming conventions, folder structures, API contracts, error handling patterns, logging standards, authentication flows, security patterns and UI design tokens: all agreed and encoded before the AI writes a single class.

The result is a modernized codebase your engineers can navigate, extend and maintain immediately - because it looks like code they would have written themselves. Only faster, more complete, more secure, and fully tested.

AdeptRecode.ai can still use local LLMs internally where approved. The product value is the governed migration process around the model - local privacy, traceability, deterministic scaffolding and human approval gates.

📐
Architecture patterns
Clean architecture, SOLID, DDD - agreed before generation
Client-configured
🔌
API contracts
OpenAPI specs, endpoint naming, versioning - standardised
Auto-generated
🔐
Secure coding patterns
OWASP-aligned, auth scaffolding, audit logging - every module
OWASP aligned
⚙️
Open-source BPM
Camunda, Flowable or jBPM - governed process definitions
Open-source
🛡
SecDevOps pipeline
SAST, SCA, secret scanning - built into CI/CD from day one
SecDevOps
📊
Data layer standards
ORM patterns, migration scripts, data dictionary - auto-documented
Auto-generated
Who we work with

For the people responsible
for systems they didn't build.

Every person here inherited a problem they didn’t create. AdeptRecode.ai gives them a governed path forward.

C
CTO / CIO
“I can’t afford another 18-month project that delivers the wrong thing.”
Modernize without betting the company on it — documented, tested, client-standard output from day one.
V
VP Engineering
“Half our capacity goes to working around the old system.”
Clear the runway with clean APIs, tested services, and architecture your team can own.
A
Head of Architecture
“I need to own the output, not just receive it.”
Define the target architecture before generation begins, with every module conforming to your patterns.
R
Compliance / Risk
“We can’t prove the system does what we think it does.”
Get traceability, audit trails, and business rule provenance generated as part of the process.
T
Transformation Consultant
“I need a differentiated offer before competitors build one.”
Bring clients an AI engine that slots into your engagement model and strengthens your modernization offer.
P
Programme Director
“We’re 18 months in and still finding things out of scope.”
Ground scope in requirements extracted from the real system before build begins.
Industries & stacks

Built for sectors where the
stakes are too high to guess.

Banking
Banking & Financial Services
Government
Government & Public Sector
Healthcare
Healthcare & Life Sciences
Energy
Utilities & Energy
Telecommunications
Telecommunications
Insurance
Insurance
COBOL COBOL
C++ C / C++
Delphi Delphi
.NET .NET Framework
Java Legacy Java 8
PowerBuilder PowerBuilder
C++ C / C++
Delphi Delphi
.NET .NET Framework
.NET .NET 8
React React + TypeScript
Python Python 3
Node Node.js
Spring Spring Boot
Java Java 21
Microservices Microservices
GraphQL REST / GraphQL
Camunda Camunda BPM
Flowable Flowable / jBPM
.NET .NET 8
React React + TypeScript
Python Python 3
Node Node.js
Get started

Four weeks.
A real system.
No guesswork.

Not a demo environment. A working proof-of-concept on an actual legacy codebase - with human-reviewed requirements before a single line of code is generated.

Start the conversation → Visit adept-view.com
1
Scope and NDA. One application or module. Measurable success criteria agreed together. Target stack, compliance requirements and BPM needs defined. Component library configured to your standards.
2
Discovery and approved BRD. All three discovery inputs run simultaneously. BRD, functional spec and business rule register generated - then reviewed and signed off by your team before build begins.
3
Architecture sign-off. Component architecture, API contracts and deployment blueprint reviewed by your architects. Approved before a single line of application code is written.
4
Parallel generation and delivery. Code and test suite generated simultaneously from the approved BRD. Full codebase, Playwright suite, SecDevOps pipeline and traceability matrix - in your target language, to your standards. Yours to keep.
Contact us

Tell us what needs
modernizing next.

Share the system, risk constraints and target outcome. Our team will shape a focused modernization conversation around your actual environment.

info@adept-view.com
NDA-friendly discovery conversations
Response within 1 business day
Your source code and documents stay controlled
Start a modernization conversation
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