Deterministic modernization
System Modernization with agentic discovery
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
Modernization outputs
- Estate baseline
- Business rules
- Target architecture
- Transformation plan
- Generated implementation
- Validation evidence
Each output keeps a thin trace through Adapts 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.
Questions Adapts answers
The hard questions behind every modernization program.
- 01
What actually happens?
Trace the full flow across programs, jobs, data, APIs and business rules.
- 02
What breaks if this changes?
See downstream and cross-application impact before implementation.
- 03
Where does this rule live?
Trace business behavior back to source-linked evidence.
- 04
What must move together?
Find tightly coupled domains and migration boundaries.
- 05
What can change independently?
Identify safer modernization seams from actual dependencies.
- 06
Did we preserve behavior?
Validate replacement systems against legacy logic and dependencies.
The journey
One context across the complete modernization journey.
Every stage shares the same Adapts model — up to date on every commit. Stages stay visible and linkable; nothing is hidden behind a carousel.
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 AdaptsWeeks of tribal-knowledge transfer and incomplete inventories.
With AdaptsA current estate map teams can query from the code itself.
Spec coverageBuild status, verified against the code.Watch demo →
Sequence diagramsArchitecture that documents itself.Watch demo →Lands in your tools: Confluence · Slack · MS Teams
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 AdaptsRoadmaps drawn from workshops, not from dependency reality.
With AdaptsA phased plan grounded in blast radius, shared services and blockers.
Modernization planningRoadmap, risks, files, draft Jira epics.Watch demo →
Boards build themselvesTickets get answered; draft epics land on your board.Watch demo →Lands in your tools: Jira · Azure Boards · Confluence
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 AdaptsCritical conditionals live only in tribal knowledge and aged COBOL.
With AdaptsEach rule links source symbol → workflow → requirement → target responsibility.
Lands in your tools: Confluence · Jira · GitHub
Build
Transform with governed agents
Specialized agents operate inside approved context and policy
Agents share one interpretation of the estate — with visible boundaries, required approvals and recorded outputs.
Before AdaptsLLMs guess at context and ship risky code.
With AdaptsAgents receive deterministic context upfront and leave an evidence trail.
Agent-native APIsDeterministic cross-repo answers.Watch demo →
Automated testsTests from real business requirements.Watch demo →Lands in your tools: Claude Code · Cursor · Copilot · GitHub · Azure DevOps
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 AdaptsDownstream impact surfaces after the incident.
With AdaptsMatching and divergent behaviour called out with source evidence before cutover.
Lands in your tools: GitHub · GitLab · Bitbucket · Azure DevOps
Release · Operate
Migrate and continuously govern
Cut over safely, then keep the model current
Pilot → parallel run → controlled cutover → validation → decommission — with Adapts refreshing on every commit.
Before AdaptsMigration ends when traffic moves; knowledge drifts again.
With AdaptsOperational context, docs and impact analysis stay aligned with the live estate.
Release intelligenceImpact, action, and risk, written for you.Watch demo →
Ticket resolutionRoot cause traced through the code graph.Watch demo →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.
Legacy parsers ingest decades of production code into one org-wide model — no manual inventory.
Modern application estate
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 living enterprise context.
Each agent has approved context, assigned responsibility, permitted tools, policies, required approval and a recorded output.
- Requirements agent
- Architecture agent
- Transformation agent
- Test agent
- Documentation agent
- Requirement approved
- Architecture proposed
- Human review
- Implementation generated
- Tests generated
- Evidence attached
Validate
Source and target behaviour, side by side.
Illustrative equivalence compare — matching steps verify; differences expose evidence for review.
Existing system
- InputVerified
- Business ruleVerified
- Data operationVerified
- OutputVerified
- Exception pathVerified
Validation layer
- Requirement coverage
- Functional tests
- Data comparison
- Security checks
- Dependency impact
- Exception-path coverage
Modernized system
- InputVerified
- Business ruleVerified
- Data operationVerified
- OutputVerified
- Exception pathReview
Cutover
Migrate with a governed timeline — then keep governing.
Modernization is continuous: after cutover, commits refresh documentation, impact analysis and operational context.
- Pilot
- Parallel run
- Controlled cutover
- Validation
- 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.
Evidence
See the evidence Adapts produces
Product visuals, labeled samples and linked case studies — not unsupported outcome metrics.
Modernization readiness
How well do you actually understand your estate?
Turn discovery into a measurable readiness score across the dimensions that determine modernization risk.
Context Readiness Score
Low visibility into dependencies and business rules is increasing modernization risk.
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.