Build a portfolio-scale AI modernization factory


Most enterprises do not have a single modernization challenge. They have a portfolio challenge.

A few legacy applications may be visible because they are expensive to maintain, difficult to change or tied to urgent transformation goals. But the real issue sits across the wider estate: aging platforms, hidden business logic, fragmented delivery tools, undocumented dependencies and teams that must modernize old systems while still shipping new products, features and experiences. Treating that as a one-app problem leads to one-off pilots, inconsistent methods and slow, expensive rework.

A more effective approach is to modernize as a factory model.

Sapient Slingshot helps enterprises build a repeatable AI-powered modernization factory that can operate across portfolios, not just individual projects. It provides a governed platform for discovery, business-rule extraction, specification-led modernization, testing and release workflows—while also supporting net-new software delivery on the same system. The result is a more scalable operating model for organizations that need to transform large application estates without losing continuity, control or delivery momentum.

Why portfolio modernization breaks down


Large-scale modernization programs often stall for the same reasons. Critical business rules are buried in legacy code. Requirements are incomplete or scattered across teams and tools. Architecture intent gets disconnected from implementation. Testing becomes manual and time-intensive. Release readiness depends on reconstructing decisions and evidence late in the process.

Those problems compound when modernization spans dozens or hundreds of applications. Every team develops its own approach to discovery. Specifications are inconsistent. Patterns are not reused. Governance becomes harder to enforce. Even when an individual pilot succeeds, the enterprise is left without a standard way to industrialize the work across the rest of the portfolio.

That is why modernization needs to be framed as an estate-wide system of delivery. The goal is not just to convert code faster. It is to create a repeatable flow from legacy understanding to modernized software, with business fidelity, testing discipline, governance and human accountability built in from the start.

Move from isolated efforts to a modernization factory


Sapient Slingshot is designed for that shift.

Built for both modernization and new software delivery, Slingshot supports the full software development lifecycle across planning, design, engineering, testing, deployment and support. Instead of relying on disconnected point tools, it orchestrates specialized agents and workflows across the lifecycle while carrying forward shared business, domain and technical context.

For modernization programs, that means teams can standardize how they:


This is what turns modernization from a series of heroic one-off efforts into a portfolio-scale factory model.

Start with discovery and business-rule extraction


Enterprise modernization is risky when teams begin by guessing what old systems do.

Slingshot helps organizations start with understanding. It can analyze legacy systems, surface dependencies and extract business logic before modern code is generated. That matters because many high-value legacy applications contain rules, validations and operational assumptions that are poorly documented or known only by a small number of experts.

By making those rules explicit earlier, teams can create a more reliable foundation for downstream architecture, development and testing. Publicis Sapient has associated Slingshot with up to 95% accuracy in business rule extraction and up to 80% less expert time required to support modernization projects. For enterprise leaders, that means scarce subject matter expertise can be used where it matters most instead of being consumed by manual reverse engineering.

Modernize through verified specifications, not rewrite guesswork


A portfolio-scale modernization factory needs a common source of truth.

Slingshot uses a specification-led approach that converts recovered business logic, rules and dependencies into reviewable specifications before downstream code generation begins. Those specifications become the thread connecting discovery, design, engineering, testing and release.

This approach helps enterprises reduce the risks of rewrite-from-scratch modernization. Instead of jumping from legacy code directly to new implementation, teams can validate intended behavior earlier, align stakeholders around what must be preserved and use specifications to guide modern architecture and code generation.

At scale, that consistency matters. It creates reusable modernization patterns across the portfolio, improves traceability between old and new systems and makes it easier to govern quality across many workstreams at once.

Standardize workflows across many applications


Modernization factories fail when every project reinvents the process.

Slingshot provides reusable workflow orchestration through a central studio environment, specialized agents and embedded developer access. Teams can configure and coordinate workflows across backlog generation, architecture, development, testing and release while applying common methods across the estate.

That includes support for:


Because workflows run with shared enterprise context, outputs do not have to be recreated from scratch at every stage or by every team. Context compounds over time. Discovery informs specifications. Specifications inform development. Development informs testing and deployment. That continuity is essential when programs need to modernize at scale without multiplying complexity.

Modernize and keep shipping on the same platform


Most enterprises cannot pause innovation while they fix the core.

They still need to launch new products, improve customer experiences, deliver new APIs and respond to market or regulatory demands. That is why Slingshot is designed for both legacy modernization and net-new software delivery on the same platform.

The same environment that supports discovery, code modernization and specification-led transformation can also support new digital products, applications, APIs and features through an AI-enabled end-to-end delivery cycle. Teams can analyze requirements, generate agile artifacts, create architecture documentation, develop code, automate testing and support deployment without switching to a separate disconnected toolchain.

This is a critical operating advantage for portfolio transformation leaders. It means modernization is no longer a side program competing with delivery. Both can happen together, on one governed platform, with one shared context foundation and one repeatable way of working.

Governance, traceability and human oversight built in


Enterprise leaders do not need more speed without visibility. They need speed with control.

Slingshot is built for governed, human-in-the-loop delivery. Organizations can control agent access, data, models and integrations while maintaining auditable records across prompts, decisions, agent runs, code, tests and release evidence. Engineers and domain experts validate outputs at defined control points instead of being removed from the process.

That model is especially important for large estates where modernization work affects business-critical systems, compliance obligations and operational resilience. Governance is not added after the fact. It is embedded in the workflows that move applications from discovery to release.

Build a repeatable operating model for enterprise transformation


The promise of AI in modernization is not a faster pilot. It is a better operating model.

With Sapient Slingshot, enterprises can move beyond isolated experiments and build a portfolio-scale AI modernization factory: one that standardizes discovery, extracts critical business rules, modernizes through verified specifications, automates testing, supports governance and keeps delivery moving across both legacy and net-new software.

Organizations using Slingshot have seen outcomes such as up to 85% first-time pass rate for generated code, up to 5x greater velocity for new feature releases after modernization, up to 50% reduction in modernization costs and modernization delivered up to 3x faster than traditional approaches. Just as important, they gain a repeatable system for scaling those improvements across the estate.

For CIOs, CTOs and transformation leaders, that is the real opportunity: not just modernizing one application well, but building the factory that can modernize many—while the business keeps shipping.