Retailers, CPG companies, and Logistics providers still rely on legacy platforms to run mission-critical operations - POS and store systems, merchandising and assortment, pricing and promotions, loyalty, e-commerce, order management, inventory visibility, demand forecasting, replenishment, warehouse management, transportation planning, and returns. These environments are not just “old systems”; they embed decades of business rules, integrations, batch orchestration, and customizations that are often only partially documented, yet essential to revenue, customer experience, and supply chain execution.
That is what makes modernization in retail, CPG, and logistics fundamentally different from many other industries. The systems that need to change are also the systems that must keep selling, shipping, and serving customers—without breaking checkout, order promising, inventory accuracy, warehouse throughput, or transportation execution.
Organizations face pressure from always-on omnichannel expectations, marketplace competition, shrinking margins, volatile demand, supply disruption, and rising fulfillment costs. Retailers must deliver consistent customer experiences across stores and digital channels while improving inventory turns and reducing stockouts. CPG firms must optimize trade spend, improve forecast accuracy, and strengthen customer collaboration while maintaining product availability. Logistics providers must increase network agility, improve on-time performance, and integrate partner ecosystems - often across heterogeneous, acquisition-driven IT landscapes. With scarce legacy SMEs and high execution risk, modernization programs can stall between business urgency and operational impact.
Before an organization can safely transform a legacy estate, it must first understand what the systems are actually doing - not just what the documentation says they should do. In retail, CPG, and logistics environments, true behaviour is often buried across custom code, integration middleware, rules engines, configuration tables, data structures, operational scripts, and fragmented SOPs. NeoZeta™, natively powered by Gemini, was designed to uncover, organize, and validate that operational reality—so modernization can proceed with confidence.
Mphasis built NeoZeta™, natively powered by Google Gemini Enterprise, to treat legacy modernizationas first a relearning problem, before it can be handed over to autonomous agents for forward engineering.
Rather than approaching modernization as a narrow code conversion exercise, NeoZeta™ applies a controls-first, intelligence-led model that helps institutions extract the embedded business logic of legacy systems and convert that understanding into a safer, more structured modernization roadmap.
For Supply-Chain and Operations leaders, NeoZeta™ preserves fulfillment accuracy, inventory integrity, and peak-season stability. For CIOs and technology leaders, NeoZeta™ reduces modernization risk, shortens release cycles, and improves traceability, governance, and audit readiness. For Engineering teams, NeoZeta™ delivers validated specifications, domain-aligned architectures, and safer paths to modern services across high-volume transaction systems.
This is where NeoZeta™, powered by Gemini, is unique and stands apart. It does not simply translate code. It relearns the legacy estate and converts that understanding into explainable artifacts that architects, engineers, and business SMEs can validate before transformation begins.
NeoZeta™ is designed to help retail, CPG, and logistics organizations accelerate discovery, reverse engineering, and modernization planning across the software delivery lifecycle—spanning customer, commerce, supply chain, and transportation domains.
By combining deterministic engineering analysis with Gemini-powered reasoning, NeoZeta™ surfaces deeply buried business and technical logic from legacy environments, including:
This is where NeoZeta™, powered by Gemini, stands apart. It does not simply translate code. It relearns the legacy estate and converts that understanding into explainable artifacts that architects, engineers, product owners, and operations SMEs can validate before transformation begins.
One of the most painful stages of retail, CPG, and logistics modernization is discovery. It is time-consuming, SME-dependent, and often incomplete—especially when knowledge is distributed across store systems, e-commerce platforms, OMS/ERP, WMS/TMS, integration layers, rules/configuration tables, data models, and outdated procedures. NeoZeta™ removes much of this black box by ingesting codebases, interface specifications, data models, configuration artifacts, batch definitions, and documentation to reconstruct how the system actually works.
This enables modernization teams to:
The result is a faster, more reliable foundation for modernization.
NeoZeta™, powered by Gemini, produces more than analysis. It generates structured artifacts that can directly support modernization planning and execution, including:
NeoZeta™ produces application structure graphs, call chains, program chains, and dependency views that help teams understand how legacy systems are wired together. This improves impact analysis and allows modernization programs to prioritize the areas of highest business, operational, or regulatory significance.
The platform can identify and document business rules, technical rules, data relationships, control logic, interface behavior, and batch flows embedded inside the codebase and surrounding artifacts. This helps convert institutional knowledge trapped in legacy systems into reusable modernization intelligence.
NeoZeta™ maps legacy behavior to real-world capabilities such as product and item master, merchandising and assortment, pricing and promotions, order management and fulfillment, inventory and replenishment, warehouse management, transportation management, supplier collaboration, and returns. Where relevant, those outputs can be aligned to industry reference models and integration standards (for example, EDI patterns) to improve standardization and accelerate target-state architecture design.
NeoZeta™ generates recommendations for modernization patterns and sequencing, prioritizing outcomes such as resiliency, scalability, maintainability, throughput, latency, data integrity, and operational continuity for high-volume retail, CPG, and logistics workloads (including seasonal peaks and promotional surges).
Where required, legacy applications can be converted into an intermediate representation that supports forward engineering into modern cloud-native stacks while preserving core business semantics and improving testability, traceability, and control evidence.
At the core of Mphasis modernization approach is an Ontology-driven knowledge graph that helps transform fragmented legacy knowledge into a connected, reusable modernization asset.
In most legacy environments, critical knowledge is scattered across code, documents, batch flows, data structures, interfaces, and tribal memory. NeoZeta™ organizes these into a structured model that links systems, workflows, business rules, controls, data, and dependencies in a way that is queryable, explainable, and reusable across the modernization lifecycle.
For retail, CPG, and logistics organizations, this is especially powerful. It creates a durable layer of enterprise understanding that can support not just discovery, but also design, testing, controls validation, impact analysis, and future change programs. It also provides a stronger bridge between legacy behavior and standards-aligned target architectures.
As we addressed above, NeoZeta™ takes a different path, by combining deterministic parsers and reasoning with generative AI, it provides institutions with explainable modernization knowledge that can be reviewed and validated before systems are changed.
This is particularly important in retail, CPG, and logistics, where defects can lead to checkout downtime, broken promotions, inventory inaccuracies, failed allocations, delayed shipments, chargebacks, higher returns, customer dissatisfaction, and revenue leakage.
The outcome is not simply migration from COBOL or other legacy stacks into Java, Python, or .NET. It is the extraction of durable business value from legacy systems and the rebuilding of that value on a stronger, more transparent, and more adaptable foundation.
Mphasis is designed NeoZeta™ to operate as part of an end-to-end modernization agentic workflow spanning relearning, planning, architecture, and delivery agents.
It starts by extracting and structuring knowledge from legacy code, batch jobs, documents, interfaces, and data definitions. That relearned intelligence can then support downstream agents and engineering workflows for target-state architecture, agile planning, specification generation, forward engineering, testing, and delivery execution.
This makes NeoZeta™ more than a discovery engine. It becomes a foundational modernization intelligence layer — one that improves decision-making, reduces ambiguity, and increases consistency across the full program lifecycle.
In retail, CPG, and logistics, modernization must be achieved without compromising security, privacy, operational resilience, or regulatory posture.
NeoZeta™ is designed to support modernization in environments containing sensitive information such as customer PII, loyalty data, payment data, supplier and contract data, shipment and tracking data, and operational performance data. Throughout the relearning and modernization process, organizations can maintain traceability, preserve control evidence, and align outputs to internal governance requirements and external obligations such as PCI DSS (where payments are in scope), privacy regulations (for example GDPR/CCPA), and broader control expectations (for example SOC 2 / SOX, where applicable).
This matters because modernization success in these industries is not only about faster delivery—it is also about proving that transformation was executed safely, transparently, and without disrupting peak trading periods, fulfillment SLAs, or customer commitments.
NeoZeta™, natively powered by Gemini Enterprise, has delivered measurable value in large-scale highly regulated Financial Services and is best positioned to accelerate Retail, CPG, and reasoning with generative AI, by compressing the discovery and relearning phase - often the longest and most SME-constrained part of transformation.
For example:
For a leading global financial technology provider on a multi-year modernization journey, Mphasis successfully used NeoZeta™ relearning agent, powered by Google Gemini, to relearn a large COBOL-based platform supporting account processing, digital banking, and payments, in 2 months, that would have typically taken 12-18 months.
The program delivered significant results:
These outcomes demonstrate how NeoZeta™, powered by Gemini, can materially compress modernization readiness timelines while reducing risk and improving transformation confidence across retail, CPG, and logistics.
Modernization for retailers, CPG firms, and logistics providers is no longer optional—and it cannot be reduced to a generic migration or a point-solution implementation.
Winning programs start with one disciplined move: relearn the legacy estate as it truly runs in production, then convert that knowledge into a structured, traceable path forward. That is where Mphasis NeoZeta™, natively powered by Google Gemini Enterprise, creates its advantage.
By combining deterministic engineering, Gemini-powered reasoning, and an ontology-driven knowledge graph, NeoZeta™ turns hidden logic into explainable modernization intelligence—accelerating discovery, strengthening audit-ready traceability, and reducing transformation risk from day one.
The result: faster modernization with confidence—preserving operational semantics, control integrity, and resilience—so organizations can improve omnichannel customer experience, pricing and promotion effectiveness, inventory accuracy and turns, warehouse throughput, on-time-in-full (OTIF) performance, and cost-to-serve.
Invite you to get started:
Mphasis offers focused NeoZeta™-led assessments and guided modernization engagements to help retailers and logistics providers move from relearning to execution with confidence. Let’s start a conversation about your operational priorities and modernization roadmap.
Chetan Korke - Retail CPG & Logistics Industry Principal
Siva Sreeraman - Head of Modernization Tribe
Nandhakumar P - VP Client Partnership Retail CPG