ASIMOV Application Modernization Strategy for Every Stage

Offerings

One Intelligence Core Across Multiple Modernization Paths

Use ASIMOV for a bounded discovery need, migration readiness, a controlled transformation wave, a program-scale modernization factory or retained target intelligence.

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The Challenge

People spend too much time searching for information, interpreting fragmented knowledge, switching between systems, and repeating routine work, all of which directly limit productivity. At the same time, enterprises are rolling out copilots and AI platforms that often lack role-specific context, trusted enterprise knowledge, or a clear adoption model. Instead of improving productivity, AI can become another tool people need to learn, verify, and work around.

What We Deliver

Role-aware AI assistance. We give employees and customers assistance across the moments where people lose time, context, and productivity: finding and applying knowledge, supporting decisions, completing common requests, and learning new ways of working with AI.
Knowledge and adoption foundation. We build the enterprise knowledge foundation and adoption model required for these capabilities to become trusted parts of everyday work and deliver sustained productivity improvement.
Trusted, grounded answers. Assistance draws on governed enterprise context rather than raw retrieval, so people get consistent, cited answers they can act on with confidence.

Documentation Only

Reconstruct application functions, business rules, dependencies and flows before you commit to a full-scale migration.

Function-level documentation
Business-rule inventory
Knowledge search
SME review packs

Discovery & Documentation

Create a connected baseline for decision-making, onboarding and future modernization.

Source graph
Dependency and impact views
Risk and complexity signals
Living knowledge base

Migration Readiness

Establish reliable scope, target mappings, sequencing and a representative proof wave.

Module segmentation
Retain/modify/replace decisions
Target gaps and dependencies
Wave plan and estimates

Full Modernization

Execute agentic transformation with continuous validation and accountable delivery.

Target code and configuration
Tests and reconciliation
Traceability and evidence
Release-ready work packages

Rationalize & Converge

Compare capabilities, rules, data and integrations across applications to simplify the estate.

Overlap analysis
Consolidation opportunities
Retirement candidates
Convergence blueprint

Maintain

Keep the target graph, specifications and evidence synchronized with application change.

Impact analysis
Developer knowledge
Drift detection
Progressive handover

Framework Modernization

Upgrade obsolete Java, .NET and related frameworks while preserving established behavior.

Mainframe & Midrange

Reconstruct COBOL, CL, RPG, batch, file and interface logic before staged modernization.

Desktop-to-Web

Move Delphi, VB and comparable desktop estates to modern web architectures.

Monolith Re-architecture

Identify boundaries and dependencies before modularization or service decomposition.

Cloud-native Modernization

Align legacy behaviour with cloud platforms, security, observability and deployment standards.

New Engineering & Enhancement

Ground new changes in existing system context, approved requirements and continuous validation.

Source intelligence and target blueprint established before migration

Agents perform the code transformation and self-correction cycle

Engineers improve agents, patterns, prompts and validation rules

Human experts govern ambiguity, architecture and release acceptance

Source intelligence and target blueprint established before migration

Agents perform the code transformation and self-correction cycle

Engineers improve agents, patterns, prompts and validation rules

Human experts govern ambiguity, architecture and release acceptance

Enterprise AI Strategy & Advisor

Shape and prioritize AI opportunities across people, processes, and products, with clear value, readiness, and execution paths.

AI-Led Legacy Modernization

Reconstruct complex applications, define the target state, and execute controlled modernization or software transformation with ASIMOV.

Forward Engineering

Carry modernized system knowledge forward into new features and services so the application can evolve without immediately rebuilding architectural debt.

Product Portfolio Rationalization

Use business and engineering evidence to decide where to invest, consolidate, re-engineer, maintain, or retire across the product portfolio.

AI-Augmented Software Engineering

Extend AI beyond coding into impact analysis, development, testing, documentation, review, and release.

SaaS Agentification & Embedded AI Features

Add intelligent capabilities and agentic experiences to existing SaaS products while respecting the product architecture, user experience, and operating constraints.

AI-Led Brownfield Support

Make complex live applications easier to understand, support, enhance, and transition toward modernization when the business is ready.

Enterprise AI Strategy & Advisory

Shape and prioritize AI opportunities across people, processes, and products, with clear value, readiness, and execution paths.

AI Copilot & Knowledge Assistants

Help people find, synthesize, compare, and apply enterprise knowledge with role-aware, source-grounded assistance.

Customer and Employee Self-service

Make routine service easier for users and lighter for service teams through grounded answers, approved actions, and context-aware human handoff.

AI Enablement and Workforce Adoption

Redesign how roles work with AI, build practical skills and confidence, and measure whether adoption is creating real productivity value.