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Deterministic modernization

Modernize complex enterprise systems without losing the business logic.

Adapts maps the existing estate, preserves business intent, governs AI-assisted transformation and traces every modernization decision back to source evidence.

Illustrative sample

Fragmented estate → governed context → structured modernization outputs

Existing estate

  • COBOL
  • Java
  • PL/I
  • APIs
  • Databases
  • Queues
  • Documents
  • Backlog
  • Infrastructure
  • COBOL
  • Java
  • PL/I
  • APIs
  • Databases
  • Queues
  • Documents
  • Backlog
  • Infrastructure
Adapts HC3Deterministic enterprise context

Modernization outputs

  • Estate baseline
  • Business rules
  • Target architecture
  • Transformation plan
  • Generated implementation
  • Validation evidence

Each output keeps a thin trace through HC3 back to the source estate.

The gap

Modernization fails when knowledge is separated from transformation.

People and time become the bottleneck — or agents work from one enterprise context.

Traditional
With Adapts

The journey

One context across the complete modernization journey.

Every stage shares the same HC3 model — up to date on every commit. Stages stay visible and linkable; nothing is hidden behind a carousel.

  1. Understand

    Discover the estate

    Map applications, dependencies, workflows and source evidence

    Expand from one repository to shared libraries, products and the organization-wide estate — before anyone guesses at scope.

    Before Adapts

    Weeks of tribal-knowledge transfer and incomplete inventories.

    With Adapts

    A current estate map teams can query from the code itself.

    Lands in your tools: Confluence · Slack · MS Teams

  2. Plan

    Define the modernization path

    Sequence work from real system relationships

    Adapts provides evidence, dependencies and architecture context for modernization decisions — teams retain disposition authority.

    Before Adapts

    Roadmaps drawn from workshops, not from dependency reality.

    With Adapts

    A phased plan grounded in blast radius, shared services and blockers.

    Lands in your tools: Jira · Azure Boards · Confluence

  3. Understand · Plan

    Preserve business intent

    Trace rules from source through requirements to target design

    Business rules are extracted with source evidence — not invented by a model without grounding.

    Before Adapts

    Critical conditionals live only in tribal knowledge and aged COBOL.

    With Adapts

    Each rule links source symbol → workflow → requirement → target responsibility.

    Lands in your tools: Confluence · Jira · GitHub

  4. Build

    Transform with governed agents

    Specialized agents operate inside approved context and policy

    Agents share one HC3 interpretation of the estate — with visible boundaries, required approvals and recorded outputs.

    Before Adapts

    LLMs guess at context and ship risky code.

    With Adapts

    Agents receive deterministic context upfront and leave an evidence trail.

    Lands in your tools: Claude Code · Cursor · Copilot · GitHub · Azure DevOps

  5. Review

    Validate behaviour and risk

    Compare source and target behaviour with shared evidence

    Requirement coverage, functional tests, data comparison and exception paths — tied back to source.

    Before Adapts

    Downstream impact surfaces after the incident.

    With Adapts

    Matching and divergent behaviour called out with source evidence before cutover.

    Lands in your tools: GitHub · GitLab · Bitbucket · Azure DevOps

  6. Release · Operate

    Migrate and continuously govern

    Cut over safely, then keep the model current

    Pilot → parallel run → controlled cutover → validation → decommission — with HC3 refreshing on every commit.

    Before Adapts

    Migration ends when traffic moves; knowledge drifts again.

    With Adapts

    Operational context, docs and impact analysis stay aligned with the live estate.

    Lands in your tools: GitHub · Azure DevOps · Jira · ServiceNow · Slack

The engine

From legacy parsers to a modern application estate.

One pipeline: ingest, graph, plan, then ship into front-end, backend, infra and tests — in the languages your teams already run.

COBOL
Legacy ParserCOBOL · Pascal · Stingray · Fortran · RPG · PL/I
Knowledge graphAlways current on every commit
Transformation planningEvidence-backed sequencing
Go
Modern applicationsFront-end · Backend · Infra · Tests

Legacy parsers ingest decades of production code into one org-wide model — no manual inventory.

Modern application estate

Front-end
TypeScript
Backend
Go
Infra
Terraform
Tests
Jest

Preserve intent

Every modernization decision traces to source evidence.

Selecting a node reveals illustrative evidence fields — the same shape teams see when reviewing grounded outputs.

Governed transformation

Agents operate around one stationary HC3 context.

Each agent has approved context, assigned responsibility, permitted tools, policies, required approval and a recorded output.

Adapts HC3Shared governed context
  • Requirements agent
  • Architecture agent
  • Transformation agent
  • Test agent
  • Documentation agent
  1. Requirement approved
  2. Architecture proposed
  3. Human review
  4. Implementation generated
  5. Tests generated
  6. Evidence attached

Validate

Source and target behaviour, side by side.

Illustrative equivalence compare — matching steps verify; differences expose evidence for review.

Existing system

  1. InputVerified
  2. Business ruleVerified
  3. Data operationVerified
  4. OutputVerified
  5. Exception pathVerified

Validation layer

  • Requirement coverage
  • Functional tests
  • Data comparison
  • Security checks
  • Dependency impact
  • Exception-path coverage

Modernized system

  1. InputVerified
  2. Business ruleVerified
  3. Data operationVerified
  4. OutputVerified
  5. Exception pathReview

Cutover

Migrate with a governed timeline — then keep governing.

Modernization is continuous: after cutover, commits refresh documentation, impact analysis and operational context.

  1. Pilot
  2. Parallel run
  3. Controlled cutover
  4. Validation
  5. Decommission
  • On-premisesRuns inside your data center boundary.
  • Air-gappedFully disconnected for the most regulated environments.
  • Private cloudYour AWS, Azure, or GCP account — you own the keys.
  • DockerContainerized delivery aligned to your pipeline.
  • KubernetesOrchestrated at estate scale.
  • OpenShiftEnterprise Kubernetes with your platform controls.

Next step

Bring one representative application.

See how Adapts maps the system, exposes critical dependencies, identifies business workflows and creates a traceable modernization path.

You provide

  • Representative application
  • Supporting repositories
  • Available documentation
  • Modernization objective

Adapts demonstrates

  • Application map
  • Dependency paths
  • Business workflows
  • Transformation boundaries
  • Traceability evidence

See it on your codebase

See it on your codebase. At the stage that matters.

A 30-minute technical walkthrough with an enterprise architect. No slides — a live demo on real code.