L’industrializzazione dell’AI Agentica nel software delivery
Artificial intelligence, governance, and measurability throughout the software lifecycle.
AI is changing software. But accelerating code development is not enough.
GenAI is increasing the productivity of development teams and making it possible to automate increasingly complex activities throughout the Software Development Lifecycle (SDLC). But local benefits do not automatically translate into scalable results. The challenge for organizations is to transform AI from an individual tool into an industrial capability: a delivery model capable of governing requirements, code, testing, releases, and operations in a repeatable and measurable way.
From AI Adoption to Agentic Delivery: A Structured Journey
Since 2024, Engineering has undertaken a structured journey to adopt AI in software delivery, deploying more than 3,000 AI licenses and achieving a stable adoption rate of approximately 75% of the population involved.
Through experimentation initiatives, enablement programs, and the collection of more than 200 signals per day for each software developer, we have systematically measured the progressive impact of AI on software development processes.
This experience has enabled us to achieve tangible results: up to a 50% reduction in release times, test coverage exceeding 80%, and technical debt identification and remediation activities reduced from weeks to just a few hours*.
Throughout this journey, we have developed a proven framework that maximizes the value of AI agents from an industrial adoption perspective, integrating them into the software development lifecycle to increase developer productivity and drastically reduce time-to-market.
COS'è INLAY?
INLAY is Engineering’s Agentic Delivery solution, designed to integrate AI within the SDLC rather than layering it on as a simple individual productivity tool.
INLAY (Intelligent Native Layer for Agentic Yield) orchestrates specialized assets, engineering disciplines, and measurement mechanisms across all phases of the SDLC: concept, design, analysis, development, testing, release & management.
With INLAY, the productivity gains enabled by artificial intelligence are transformed into a scalable, governed, and measurable delivery capability.
Quality and control
Integrated governance, verification mechanisms, and engineering disciplines help ensure traceability, reliability, and compliance throughout the entire software lifecycle.
More effective modernization
Greater ability to understand existing systems, reduce technical debt, and accelerate the evolution of the application landscape.
Measurable results
Metrics and monitoring tools make it possible to objectively assess the impact achieved, transforming AI adoption into a governed, value-oriented journey.
What are the benefits for customers?
The use of INLAY by Engineering teams translates into tangible benefits for organizations that entrust us with the evolution and management of their software systems.
Faster delivery
Reduced time required to analyze, design, develop, test, and modernize applications.
Solutions better aligned with the context
Agentic AI operates using the customer's information assets, requirements, and specific characteristics, enabling a higher level of personalization than standardized approaches.
One Framework. Three Transformation Paths. One Governance Model.
Specialized assets and repeatable paths, integrated with engineering disciplines, ensure the traceability, verifiability, and manageability of every outcome throughout the Delivery Journey.
01
02
03
An AI-Powered Accelerator Ecosystem for Enterprise-Scale Software Development
A dedicated AI-powered tool for every stage of the development lifecycle, from ideation to production, operating as a single integrated system rather than a collection of disconnected tools.
Our numbers
*Results measured across use cases between 2025 and 2026. Source: Engineering analysis based on project delivery data.
0
%
reduction in delivery time
0
%
increase in test coverage
0
%
faster identification of regressions
0
x
faster technical debt remediation
Agentic Delivery Applied to Business Processes
Billing: Optimization and evolution of billing systems, with enhanced capabilities for requirements analysis, testing, and regression management.
Digital Platform Management: Support for the governance and evolution of complex digital platforms involving multiple teams and multiple releases, with greater traceability throughout the entire lifecycle.
Reverse Engineering for Shadow AI: Analysis and reconstruction of AI applications or components developed outside structured processes, helping bring knowledge, control, and governance back within the enterprise perimeter.
Accounting: Modernization and evolutionary maintenance of mission-critical administrative and accounting applications, preserving operational continuity, quality, and process compliance.
Governance by design
The distinguishing element of Engineering’s approach is its ability to transform AI from a point solution accelerator into a delivery discipline. The framework combines agentic assets and engineering practices that make requirements, prompts, outputs, and decisions more structured, verifiable, and traceable.
EARS (Easy Approach to Requirements Syntax). Requirements are expressed using a structured syntax that is clearer, more verifiable, and easier to interpret within AI-driven workflows.
SPDD (Structured Prompt-Driven Development). Prompts are treated as true delivery assets: versioned, reusable, verifiable, and maintained in alignment with the generated code.
Requirements-as-Code. Requirements are managed using code-like practices, including versioning, reviews, and traceability of their evolution.
Human-in-the-Reasoning Approach. Human oversight is embedded within reasoning processes to support validation, control, and decision-making throughout AI-enabled delivery activities.
Compass. Governance, measurement, AI guardrails, and benchmarking distributed across the entire SDLC.
We accelerate the software lifecycle through agentic AI, engineering governance, and a proprietary framework developed by Engineering. We support organizations in the design, evolution, and management of customized software solutions, integrating AI directly into delivery processes. The result is a faster, more controlled, and more measurable way to transform application complexity, legacy systems, and business requirements into high-quality software.
FAQ
Reducing delivery timelines requires structured and measurable processes. With INLAY, the Agentic Delivery framework from Eng Modernize, AI agents support analysis, design, development, testing, and application management while maintaining governance, control, and quality throughout the entire Software Development Lifecycle (SDLC).
AI adoption generates value only when it becomes a scalable and governed process. INLAY industrializes the use of AI in software delivery through an ecosystem of specialized agents, structured methodologies, performance monitoring, and governance tools that make benefits measurable, repeatable, and sustainable over time.
Integrating AI into development processes requires a gradual and governed approach. INLAY introduces AI agents directly into the Software Development Lifecycle, working alongside existing people, processes, and tools without requiring radical change. Through governance frameworks, structured methodologies, and performance controls, organizations can adopt AI while maintaining operational continuity, quality, and security.
Many organizations achieve promising results through early Generative AI pilots but struggle to scale them across the enterprise. INLAY was designed to close this gap, transforming isolated initiatives into a governed and repeatable operating model. Through specialized agents, centralized governance, performance metrics, and structured adoption programs, AI becomes a delivery capability embedded within business processes and measurable over time.
Recommended for you
Explore additional content associated with the topic
