Build a Portfolio-Scale AI Modernization Factory

Across large organizations, dozens or even hundreds of legacy applications consume budget, slow delivery and trap critical business logic in aging code, disconnected documentation and institutional memory. At the same time, business leaders still expect new products, new APIs, new digital journeys and faster releases. The challenge is not simply how to modernize one system. It is how to industrialize modernization across an application estate while teams continue to ship new software.

Sapient Slingshot is built for that reality. It is an enterprise AI software development and modernization platform designed to support the full software development lifecycle across modernization and net-new delivery. By combining code discovery, business-rule extraction, specification-led transformation, testing automation, workflow orchestration and enterprise governance, Slingshot helps organizations turn isolated modernization efforts into a repeatable modernization factory.

From one-off projects to a modernization operating model

Point tools can help accelerate individual tasks. A coding assistant may speed up boilerplate. A migration utility may handle one conversion path. A pilot may prove that AI can generate code faster than a manual team. But portfolio-scale transformation requires more than isolated wins. It requires continuity across planning, discovery, design, engineering, testing, deployment and run.

That is where many modernization programs break down. Requirements are incomplete. Business rules are buried in old systems. Architecture intent gets separated from implementation. QA teams have to infer expected behavior. Release evidence is assembled late. As the number of applications grows, inconsistency and rework multiply.

Slingshot addresses that delivery-system problem by connecting the lifecycle as one governed, context-aware system. Instead of treating modernization as a sequence of disconnected handoffs, it creates a repeatable path from legacy discovery to production-ready modern software.

Why portfolio modernization starts with shared enterprise context

At portfolio scale, modernization cannot depend on each team rediscovering the same rules, dependencies and patterns from scratch. Organizations need a shared foundation that carries business, domain and technical knowledge forward across programs.

Slingshot’s enterprise context graph provides that foundation. It acts as a living map of repositories, specifications, business logic, architecture, dependencies, user journeys, data and telemetry. This shared context helps AI agents reason with greater accuracy, preserve continuity across workflows and keep outputs tied to how the business actually operates.

For transformation leaders, that matters in three ways. First, it improves prioritization by making dependencies, risks and downstream impacts more visible across the estate. Second, it supports standardization by giving teams a common context layer, reusable prompt assets and consistent workflow patterns. Third, it enables scale by letting modernization knowledge compound over time instead of being recreated application by application.

Industrialize the factory: discovery, extraction, specification, transformation

Slingshot starts upstream with code discovery and analysis. Specialized agents can examine existing systems, uncover hidden dependencies and support rationalization of what should be retained, refactored, replatformed or rebuilt. This is especially important when applications are tightly coupled, poorly documented or dependent on scarce subject matter experts.

From there, Slingshot helps extract business rules, process flows, validation logic and data structures from legacy systems. Instead of jumping directly from old code to new code, the platform uses a specification-led approach: hidden logic is converted into reviewable, testable specifications that become the source of truth for downstream work.

That specification layer is what makes modernization more repeatable and less risky. Architecture can be generated with clearer intent. Code generation can be measured against preserved rules. Teams can validate whether modernized applications behave as intended rather than relying on assumptions or incomplete documentation.

Specialized agents for every stage of portfolio execution

A modernization factory needs more than one assistant. It needs specialized agents aligned to different lifecycle tasks and modernization patterns.

Slingshot brings together agents and AI assistants across backlog creation, sprint orchestration, pair programming, code modernization, quality engineering, deployment and support. Its broader agent ecosystem includes capabilities for code discovery, semantic pull request review, API lifecycle automation, database migration and refactoring, CI/CD pipeline creation and governance, root-cause analysis and targeted modernization for specific legacy technologies.

Because these agents work within a shared enterprise context, they do not operate as isolated tools. Discovery informs backlog priorities. Extracted rules inform specifications. Specifications guide code generation. Code changes connect to automated testing, release workflows and operational support. This orchestration is what allows enterprises to scale modernization across a portfolio instead of optimizing one task at a time.

Keep shipping while you modernize

Transformation leaders rarely get to pause the business while legacy systems catch up. New products still need to launch. Features still need to ship. Customer and regulatory demands still evolve.

Slingshot supports modernization and net-new software delivery on the same platform. Teams can generate epics, stories and acceptance criteria for new work, develop applications and APIs, automate testing, support deployment workflows and carry context into operations—all while modernization programs continue in parallel.

That matters because the real goal is not just to reduce technical debt. It is to improve enterprise throughput. With shared context, reusable workflows and specialized agents, organizations can modernize core systems without forcing product teams to wait for a multi-year transformation to finish before they deliver value.

Testing automation and governance built into the factory

At portfolio scale, speed without control creates risk. Slingshot is designed to embed governance, traceability and human oversight directly into the operating model.

Quality engineering agents can generate test scenarios, test data and automation code, while supporting functional, security and performance testing. The platform can also help analyze regression impact, defects and release readiness. This reduces manual QA burden while improving coverage and consistency across applications.

Governance is built into the workflow through controlled agent access, model and data controls, human validation at defined checkpoints and auditable records across prompts, decisions, agent runs, code, tests and release evidence. For CIOs and transformation leaders, this creates a stronger chain of custody from business intent to modernization output to release decision.

Designed for enterprise scale, not isolated experiments

Slingshot has been deployed with more than 100 enterprise customers and is built to fit existing toolchains, cloud platforms and delivery environments, including private cloud, on-premises and hybrid managed-services models. It supports over 80% of major programming languages and frameworks and is designed to integrate with existing development tools, repositories and project systems.

Organizations using Slingshot have seen outcomes such as up to 95% accuracy in business rule extraction, up to 85% first-time pass rates for generated code, up to 5x faster new feature velocity after modernization, up to 50% lower modernization costs and modernization delivered up to 3x faster than traditional approaches.

Those outcomes are not just about faster code. They reflect a different operating model: one in which modernization is standardized, governed and scalable across the portfolio.

People plus platform

A portfolio-scale modernization factory is not a self-running black box. It requires experienced people who can frame the right use cases, govern workflows, validate outputs and guide transformation decisions.

That is why Publicis Sapient combines Slingshot with expert teams who help design, implement and operate AI-assisted delivery workflows. Human teams remain in control of architecture decisions, business-rule validation, quality thresholds and release readiness. The platform accelerates the work. Experienced practitioners make sure it delivers enterprise value.

Modernize the estate without losing momentum

If your challenge is one application, a point solution may help. If your challenge is an estate of legacy systems, overlapping dependencies and constant pressure to ship, you need a modernization factory.

Sapient Slingshot helps enterprises move from one-off modernization projects to a portfolio-scale operating model—using shared enterprise context, specialized agents, specification-led transformation, automated testing, workflow orchestration and built-in governance to modernize with speed, repeatability and control.

That is how organizations can modernize across the portfolio while still building what comes next.