Capability · Code Modernization

Agentic Code Modernization

Modernizing mission-critical legacy systems at machine speed — without losing mission knowledge. Hierarchical AI agent teams analyze, re-architect, and rewrite decades-old code with full functional parity and zero downtime.

  • Eliminate end-of-life vulnerabilities and all known CVEs
  • Parallel agent execution across backend, frontend, and integration domains
  • Secure LLM options — local on-prem, air-gapped, or FedRAMP-authorized cloud
  • Automated test generation — unit, functional, and trace-based parity validation
  • SDLC integration — Jira, DOORS, Azure DevOps, ServiceNow
  • Comprehensive documentation — ICD, SBOM, eMASS packages, ATO evidence
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10M+Source lines of code modernized
100%Functional parity before deployment
$30M+Demonstrated ROI for DoD customers
10×Faster than manual refactoring

Overview

Decades of mission knowledge, made legible

We modernize mission-critical legacy applications using AI-driven analysis and automation — letting agencies understand, refactor, and retire technical debt without losing institutional knowledge.

Legacy understanding at scale

From opaque codebases to searchable knowledge.

AI agents parse millions of lines of COBOL, C, JCL, and IDEAL — alongside documentation — into searchable knowledge graphs and living documentation.

Modernization readiness

Baselines that accelerate the path forward.

Generate technical and functional baselines that accelerate refactoring, migration, and re-platforming — cutting timelines by up to 10× compared to manual effort.

Audit-safe transformation

Compliance and knowledge preserved throughout.

Full traceability from legacy logic to modern outputs, with validated results and living documentation that preserve compliance and institutional knowledge.

Platform architecture

Hierarchical agent orchestration

Rather than a single AI processing an entire codebase at once, Invoke deploys specialized teams of agents — each with a defined role, explicit instructions, and quality-gated outputs — working in coordinated parallel.

Orchestrator agent

Manages requirements, enforces compliance, and coordinates all agent activity.

SBOM generation · ATO evidence · Jira / DOORS
Architect agent + research sub-agent

Deep legacy code analysis, architecture documentation, modernization planning, and ICD generation.

Multi-strategy review · Cross-validation · Microservice decomposition
Backend agents
  • Planning agent
  • Development agent
  • QA & test agent
Legacy services and APIs
Frontend agents
  • Planning agent
  • Development agent
  • QA & test agent
UI and presentation layer
Integration agents
  • Planning agent
  • Development agent
  • QA & test agent
APIs, data, and microservices

Orchestrator agent

Central command across the lifecycle.

  • Codebase ingestion and SBOM generation
  • DISA STIG, NIST 800-53, and FedRAMP enforcement
  • Jira/DOORS ticket lifecycle management
  • eMASS and ATO evidence package generation

Architect + research agent

Blueprints built from legacy logic.

  • Five-pass multi-strategy review, adversarial through synthesis
  • Interface Control Document generation
  • Microservice decomposition planning
  • Cross-validation between concern groups

Code agents, in parallel

Three sub-agents per functional domain.

  • Planning: task sequencing from architecture specs
  • Development: code rewrite and refactor
  • QA: trace-based parity tests and regression prevention

Modernization process

From legacy codebase to modern system

A structured, phased engagement from initial assessment through live deployment — with human oversight checkpoints at every stage.

  1. 01

    Ingest & analyze

    The orchestrator ingests the legacy codebase, generates an SBOM, and builds a knowledge graph of code relationships.

    2–4 weeks
  2. 02

    Research & plan

    The architect agent runs concern-group analysis and multi-strategy review, producing detailed modernization requirements.

    2–6 weeks
  3. 03

    Parallel execution

    Code agent trios execute across all functional domains simultaneously, with continuous validation.

    3–12 months
  4. 04

    QA & parity

    Automated test suites confirm full functional parity. Remediation agents fix failures without restarting the pipeline.

    Continuous
  5. 05

    Handoff & transition

    Knowledge transfer, ATO evidence packages, and operational support through final deployment.

    2–4 weeks

Language coverage

Legacy in. Modern out.

Legacy languages & stacks

  • COBOL
  • IDEAL
  • PL/I
  • FORTRAN
  • RPG
  • CICS
  • JCL
  • VB6
  • ColdFusion
  • Legacy Java EE
  • Classic ASP
  • PowerBuilder

Modern target platforms

  • Java 21 / Spring Boot
  • Python 3.12
  • TypeScript
  • React / Angular
  • Node.js
  • Go
  • Rust
  • Kubernetes
  • REST / GraphQL
  • Microservices
  • AWS / Azure GovCloud
  • Cloud-native

Before & after

The same business rule, rewritten

A payroll calculation carried forward from COBOL into modern Java — overflow-safe, testable, and documented.

Legacy COBOLBefore
1IDENTIFICATION DIVISION.2PROGRAM-ID. CALC-PAYROLL.3DATA DIVISION.4  01 WS-GROSS-PAY PIC 9(7)V99.5  01 WS-TAX-RATE  PIC V99 VALUE .22.6PROCEDURE DIVISION.7    COMPUTE WS-NET = WS-GROSS -   * no overflow check8            WS-GROSS * WS-TAX-RATE.9    STOP RUN.
Modern Java 21After
1public record PayrollResult(2    BigDecimal gross, BigDecimal net) {}34public class PayrollCalculator {5  private static final BigDecimal6    TAX = new BigDecimal("0.22");78  public PayrollResult calc(9      BigDecimal gross) {10    var net = gross.subtract(11        gross.multiply(TAX));12    return new PayrollResult(gross, net);13  }14}

Quality assurance

Multi-strategy review architecture

Each requirement passes through five sequential review iterations, each using a different strategy — eliminating the blind spots that plague single-pass AI review.

Adversarial

Actively seeks errors, omissions, and incorrect assumptions.

Completeness

Ensures full coverage — every requirement has context and citations.

Edge cases

Uncovers indirect, implicit, and boundary-condition connections.

Domain expert

Applies business context — mission-critical logic that is not obvious from the code.

Synthesis

Resolves contradictions, removes duplicates, and confirms consistency.

Automated validation — eight verification rules

  1. 1
    Coverage

    Every requirement has full context

  2. 2
    Citations

    All requirements cite source programs

  3. 3
    Citation validity

    All citations resolve to real programs

  4. 4
    Bidirectional relevance

    Citations genuinely relate to requirements

  5. 5
    Consistency

    No internal contradictions in outputs

  6. 6
    Completeness

    Every summary chunk was processed

  7. 7
    Cross-reference

    The same program is described consistently

  8. 8
    No empty fields

    All required fields are populated

Outcomes & ROI

Measurable results for mission-critical systems

Cost reduction

  • 60–80% reduction in ongoing maintenance costs
  • 40–60% infrastructure savings through cloud-native modernization
  • Developers freed from legacy maintenance for strategic mission work

Accelerated delivery

  • Parallel execution across every functional domain at once
  • Phased rollout that minimizes operational disruption
  • Continuous validation instead of a single big-bang cutover

Knowledge preservation

  • Auto-generated documentation, architecture diagrams, and ICDs
  • Institutional knowledge captured for new-developer onboarding
  • A durable record that supports ATO packages

Strengthened security

  • Eliminates all known CVEs in the legacy codebase
  • Modern frameworks with active patching
  • Full compliance with DISA STIG, NIST 800-53, and FedRAMP

Risk management

Built-in risk mitigation

Domain knowledge preservation

Risk. Loss of critical system understanding and mission-critical business logic during modernization.

Mitigation. Trace-based testing captures all system behaviors, and living documentation preserves institutional knowledge throughout.

Regression prevention

Risk. Modernized code introduces bugs or breaks existing mission-critical functionality.

Mitigation. Continuous automated validation with self-guarding agents, and full functional parity testing before any deployment approval.

Security exposure

Risk. Sensitive code or classified intellectual property exposed during modernization.

Mitigation. Local or FedRAMP-authorized LLMs only, with code scanning, malware detection, and Zero Trust architecture enforced throughout.

Oversight bottlenecks

Risk. Human review requirements slow modernization to unacceptable levels.

Mitigation. Human-in-the-loop via Jira with configurable approval tiers — only high and critical changes require sign-off, so automated execution continues unblocked.

Deployment & integration

Meets you where you operate

On-premises / air-gapped

Complete air-gapped operation with local LLM models — built for classified environments requiring full isolation.

Hybrid cloud

Secure API integration with FedRAMP-authorized services while maintaining strict data sovereignty and compliance.

Government cloud

Native deployment within AWS GovCloud, Azure Government, or other authorized environments with a full compliance posture.

DevSecOps integration

CI/CD pipeline integration with GitLab, GitHub, and Jenkins, alongside automated security scanning tools.

Agile workflow support

Native Jira, Azure DevOps, and ServiceNow integration for ticket management and end-to-end traceability.

Compliance reporting

Automated eMASS packages, security assessment documentation, and Authority to Operate evidence packages.

Typical engagement

From assessment to deployment

  1. 01

    Assessment phase

    Code baseline, SBOM generation, architectural analysis, and modernization roadmap development.

    2–4 weeks
  2. 02

    Pilot phase

    Modernize a representative module, validate the approach, refine agent configurations, and establish benchmarks.

    4–8 weeks
  3. 03

    Full execution

    Parallel modernization across all domains with continuous testing, documentation, and stakeholder reviews.

    3–12 months
  4. 04

    Transition & handoff

    Final validation, knowledge transfer, deployment support, and full ATO evidence package delivery.

    2–4 weeks

Proven in mission

10M+ source lines modernized for the U.S. Air Force

Delivered for the Air Force Life Cycle Management Center and Air Force Sustainment Command — transforming legacy COBOL, C, JCL, and IDEAL into modernization-ready baselines.

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