Automations
This pillar focuses on modernization workflows that parse undocumented legacy systems, map business logic, generate target services, and build test harnesses for safer migration. The content should show how custom translation automation reduces transformation risk, accelerates migration planning, and supports phased replacement of aging enterprise systems.
This foundational page details a custom, end-to-end agentic workflow that orchestrates the discovery, analysis, refactoring, and validation of legacy systems into modern architectures. It explains how multi-agent systems reduce transformation risk and accelerate planning by automating the mapping of business logic, generation of target services, and creation of test harnesses, directly linking the architecture to faster, safer migration timelines.
This page covers the custom workflow for automatically scanning, parsing, and cataloging undocumented legacy applications across mainframes, servers, and repositories. It details how agentic discovery reduces months of manual inventory effort, creates a system-of-record for modernization planning, and integrates with CMDBs and architecture tools to establish a reliable foundation for migration.
This page explains the custom AI workflow for parsing spaghetti code, comments, and configuration files to isolate and document core business rules and decision logic. It shows how this automation prevents critical logic from being lost during migration, reduces analyst toil, and outputs structured specifications that feed directly into service design and test generation phases.
This page details the automated workflow for analyzing legacy VSAM, IMS, or hierarchical databases to infer relationships, constraints, and business meaning, then generating modern SQL or NoSQL schemas. It covers how this automation de-risks data migration, ensures referential integrity is preserved, and accelerates the design of cloud-native data layers.
This page describes the custom orchestration workflow that analyzes monolithic application call graphs and data flows to recommend bounded contexts and automatically generate service boundary definitions. It explains how this AI-driven decomposition reduces architectural debate, creates a phased slicing plan, and outputs initial service stubs and API contracts for development teams.
This page provides a blueprint for a custom, multi-agent system that parses COBOL copybooks, procedural divisions, and JCL, then generates functionally equivalent Java services with Spring Boot frameworks. It focuses on preserving business logic accuracy, handling mainframe-specific constructs, and integrating the output into CI/CD pipelines for enterprise banking and insurance migrations.
This page outlines the specialized automation workflow for translating RPG logic, DDS files, and CL programs into modern stateless services deployable on Kubernetes. It addresses the unique challenges of IBM i modernization, showing how automated translation reduces reliance on scarce skills and enables a gradual shift from green-screen applications to API-driven architectures.
This page details the custom workflow for analyzing and refactoring custom ABAP programs within legacy SAP ECC systems for migration to S/4HANA or external microservices. It explains how automation identifies obsolete transactions, extracts business logic, and generates clean code that aligns with SAP's clean core principles, reducing upgrade cost and complexity.
This industry-specific page covers the end-to-end automation for modernizing core banking systems (like CICS/IMS transactions and batch jobs) into cloud-resilient services. It details how the workflow addresses regulatory logic preservation, high-volume transaction integrity, and integration with modern payment channels, directly tying the build to operational risk reduction and IT cost savings.
This page explains the custom workflow for migrating legacy clinical systems (e.g., MUMPS-based VistA) to modern, interoperable platforms while preserving complex patient logic and HIPAA compliance. It focuses on automating the extraction of clinical decision rules, visit workflows, and data migration to reduce patient safety risk and accelerate the transition to cloud-based EHRs.
This page details the automation architecture for decomposing monolithic telecom billing systems (e.g., legacy BRM or custom solutions) into modular, event-driven services. It covers the automated translation of rating, charging, and invoicing logic, and how the workflow ensures revenue assurance and integrates with new digital partner ecosystems.
This page outlines the custom workflow for translating legacy, on-premise MES logic controlling shop-floor operations into modern, IIoT-connected microservices. It explains how automation preserves critical production recipes, quality checks, and machine integration logic, enabling a phased migration that minimizes plant downtime and supports Industry 4.0 initiatives.
This page describes the AI workflow that analyzes legacy COBOL or shell script batch processes, maps their dependencies and schedules, and redesigns them as cloud-native, event-triggered services. It shows how this automation eliminates nightly batch windows, improves operational responsiveness, and generates the necessary orchestration code (e.g., AWS Step Functions, Azure Durable Functions).
This page covers the custom automation for modernizing high-stakes reconciliation engines that match transactions across ledgers. It details how agents extract matching rules, tolerance logic, and exception handling from legacy code to generate auditable, scalable reconciliation microservices, reducing errors and closing cycle times for finance teams.
This page explains the workflow for automating the migration of legacy HR/payroll systems, focusing on the precise translation of complex tax calculations, benefits accruals, and compliance rules. It addresses how automation ensures regulatory accuracy across jurisdictions and generates APIs for integration with modern HCM platforms like Workday or SAP SuccessFactors.
This risk-focused page details the custom workflow that identifies, tags, and validates regulatory logic (e.g., for Basel III, SOX, GDPR) within legacy code during translation. It explains how this automation creates an audit trail, ensures rules are not diluted in the new system, and reduces compliance certification overhead during migration projects.
This page outlines the automated workflow that scans legacy code for known vulnerabilities (e.g., SQL injection, buffer overflows), correlates findings with threat databases, and generates patched or refactored code in the target language. It shows how this builds security into the modernization pipeline, reducing remediation costs and improving the posture of the new system.
This page describes the automation for converting legacy flat-file, FTP, and EDI batch integrations into real-time API contracts and event streams. It covers the analysis of file layouts and processing logic to generate OpenAPI specs, message schemas, and adapter code, enabling faster partner onboarding and decomposing monolithic integration hubs.
This data-focused page details the automated workflow for analyzing legacy non-relational data structures, inferring access patterns, and designing optimal modern data models. It explains how agents generate migration scripts, data validation suites, and new application data access layers, reducing the risk and manual effort of large-scale mainframe data migration.
This QA page covers the custom workflow that uses the extracted business logic from legacy systems to automatically generate comprehensive unit test suites for the newly created microservices. It details how this automation ensures behavioral equivalence, provides immediate test coverage for refactored code, and integrates into the CI/CD pipeline to catch regressions early.
This page explains the automation for analyzing end-to-end transaction paths in a legacy monolith and automatically generating integration test scenarios for the new distributed architecture. It shows how this workflow validates service interactions, data consistency, and error handling, reducing the manual effort of building integration test harnesses from scratch.
This page details the custom workflow that automates the creation of performance benchmarks, executes load tests against both legacy and modernized systems, and compares metrics to validate non-functional requirements are met. It focuses on ensuring the new architecture meets or exceeds throughput and latency SLAs before cutover.
This page describes the automation that analyzes legacy system requirements (e.g., mainframe LPARs, mid-tier server specs) and generates cloud-agnostic IaC templates (Terraform, CloudFormation). It shows how this workflow codifies infrastructure needs, ensures consistency, and accelerates the environment provisioning phase of a modernization program.
This UX-focused page details the workflow that automatically analyzes 3270/5250 screen maps and flow logic to generate modern web UI components and navigation state machines. It explains how this automation preserves complex user workflows while delivering a contemporary interface, dramatically reducing the front-end development effort for mainframe application renewal.
This technology-specific page covers the custom automation for translating VB6 forms, COM components, and business logic into modern .NET Core APIs and Blazor or React front-ends. It addresses challenges like state management and third-party control replacement, providing a blueprint for modernizing desktop applications that are costly to maintain.
This page outlines the automated workflow for decomposing Oracle Forms modules (PL/SQL triggers, form blocks) into a modern stack of reactive front-end applications and backend REST APIs. It focuses on preserving complex data validation and master-detail relationships while enabling a cloud-hosted, scalable architecture.
This page details the workflow for automatically parsing Crystal Reports files, extracting SQL queries and formatting logic, and generating modern BI tool artifacts (e.g., Power BI datasets, Tableau workbooks) or API-driven reporting services. It shows how this automation unlocks legacy report logic for self-service analytics without manual redevelopment.
This page covers the custom orchestration workflow that manages the gradual cutover from legacy to modernized services, including dark launches, canary analysis, and traffic routing based on real-time metrics. It explains how this automation de-risks big-bang migrations, allows for rollback at a granular level, and provides operational control during the transition.
This page outlines the workflow that uses AI agents to analyze newly generated services and automatically produce architecture diagrams, API documentation, deployment guides, and runbooks. It shows how this automation closes the documentation gap that often plagues migration projects, reducing knowledge transfer time for operations and support teams.
This page explains the custom workflow that scans legacy and modernized codebases to automatically identify, categorize, and score technical debt (e.g., complexity, duplication, outdated libraries). It provides architecture leaders with a data-driven backlog for post-migration optimization, linking technical metrics to business impact and remediation effort.
This industry page details the specialized automation workflow for modernizing government systems (often written in Ada, COBOL) with a focus on preserving stringent compliance, audit trail, and accessibility (Section 508) requirements. It explains how the workflow integrates with government DevOps (GovCloud, IL5/6) and security frameworks to accelerate modernization while maintaining regulatory posture.
This page covers the automation for migrating legacy SCADA and grid control systems (often C/C++, proprietary protocols) to modern, IP-based OT/IT convergent architectures. It focuses on the precise translation of control logic, alarm handling, and real-time data processing to ensure grid reliability and safety during the technology transition.
This governance page details the workflow for extracting and modernizing the embedded change management, segregation of duties, and approval logic from legacy systems into externalized workflow engines (e.g., Camunda, ServiceNow). It shows how this automation preserves business controls while making them more agile and auditable in the new environment.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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