BrillioOne.ai breaks the legacy deadlock with AI-driven application modernization

CIOs face a persistent challenge: modernizing enterprise software systems quickly, cost-effectively, and with minimal disruption. This imperative for change comes as no surprise to CIOs and IT leaders who have long grappled with the limitations of outdated infrastructure. However, the emergence of generative AI and advanced automation tools has shifted the paradigm, offering a new approach to this perennial problem.

A recent HFS study found that CIOs overwhelmingly expect AI and automation to play a crucial role in their software engineering efforts. As shown in Exhibit 1, 93% of enterprise IT leaders see GenAI as a boost to addressing new and legacy software efforts. However, the tools are only one aspect; these firms are also rethinking how they organize their software teams and partnerships to deliver desired business outcomes.

Exhibit 1: CIOs are turning to GenAI to support application modernization and software engineering

Sample: n=200 Global 2000 firms
Source: HFS Research, 2024

This point of view looks at how Brillio and a large brokerage firm are leveraging AI and automation tools as part of their new software engineering DNA. It also shows how, when properly deployed, AI and automation can boost productivity, drive outcomes, and provide a best-in-class continuous improvement model.

Traditional SDLCs are stifling enterprise agility in the age of AI, requiring a fundamental shift in application modernization approaches

For decades, enterprises have relied on software development lifecycles (SDLC) to provide milestones for building, testing, deploying, maintaining, and updating their applications. While structured and familiar, this approach has become a significant bottleneck in the age of AI and rapid digital transformation. Sticking with traditional resource-centric SDLCs alone too often results in slow development cycles, increased technical debt, and a struggle to keep pace with evolving business needs.

The limitations of traditional SDLCs are particularly evident in the challenges associated with modernizing legacy systems, which form the backbone of many large enterprises. Too many core business systems are running on outdated code and monolithic architectures. These systems are increasingly complex to maintain, scale, and integrate with modern cloud-native applications. The result is a growing gap between an organization’s technological capabilities and business ambitions. Adding to the problem, the costs of maintaining these legacy assets often exceed the value they are creating.

While many new software development trends sought to address this, they typically only chipped away at the edge as discovery, migration, and retiring legacy code—often lacking proper documentation—was costly and cumbersome. The result was living with the devil you knew. Then, generative AI entered the equation, enabling resource-constrained services firms to harness these models’ ability to assess, document, and convert code. These tools can automate 40-70% of conversion—a significant boon for firms with limited IT resources. The human element wasn’t the roadblock; now, software engineers could apply business context to the new code throughout the SDLC rather than only at the beginning and end of the process. An example of AI-enabled solutions for automating the conversion of legacy systems to modern cloud-centric applications is Brillio’s BrillioOne.ai.

A shift in how teams approach software development is a necessary change that must happen before tools are applied

The transition from linear SDLCs to what HFS Research terms the “honeycomb” model represents a fundamental shift in how enterprises approach software development and modernization (see Exhibit 2). This new model, enabled by generative AI platforms such as BrillioOne.ai, enables simultaneous progress across multiple development areas, breaking down the silos that have long hampered efficiency and innovation.

Exhibit 2: Software development should represent a reorganization of activity over a linear progression

Source: HFS Research, 2024

This model represents a paradigm shift for software development. Unlike the linear model, where one stage leads to the next, this mindset shift allows for simultaneous progress across multiple areas, enabling constant communication and iteration between different aspects of development. Adopting GenAI tools further accelerates the outcome of this new mindset.

To accelerate software development, BrillioOne.ai makes AI and automation essential components of a modern SDLC

BrillioOne.ai provides a comprehensive suite of AI-driven tools and automation capabilities to meet its customers’ needs and modernize their applications. The platform leverages generative AI to enhance and accelerate various stages of the SDLC, including the discovery, mapping, conversation, and testing phases of software development. BrillioOne.ai enables enterprises to modernize their legacy applications while adopting more agile, flexible operations by implementing a dynamic model for the SDLC. The platform’s features include:

• Automated agile software development lifecycles (SDLC)
• AI-enhanced sprint planning and code generation
• Continuous integration/continuous delivery (CI/CD) support
• Delivery dashboard that captures 360-degree customer sentiment in near-real time by combining customer pulse, ALM telemetry, and engagement team reports

Automating agile is important because the tool can prompt or be prompted by a human-in-the-middle approach. Promoting the following best actions or resolving conflicts in a more timely manner. With AI-enhancing talent, companies are beholden to finding code developers with unique or bespoke talents.

Brillio maps its software engineering programs across planning, building, and realizing value for its clients. Then, it embeds AI and automation to drive stakeholder engagement, improve the experience, and adapt to real-time feedback. This methodology can quickly adapt resource allocation from internal and external resources to deliver continuous improvement. Finally, Exhibit 3 shows how this approach makes the CI/CD more effective as the AI tools can continue monitoring, documenting, and reporting where systems can be optimized.

Exhibit 3: With AI and automation, BrillioOne.ai drives outcomes across planning, building, and adopting new software-based solutions across an organization

Source: Brillio, 2024

BrillioOne.ai’s AI and automation approach to software engineering is relevant for enterprises with all types of IT landscapes. It integrates seamlessly with existing systems and ensures compliance with industry standards. Brillio has purposefully developed BrillioOne.ai to work across multiple codes and architectures and to package and develop SaaS software solutions. However, the focus is on creating value from the business outcomes enabled by the right combination of tools and people.

Global real estate firm adopts BrillioOne.ai to unlock agility, positioning software modernization as a business enabler

One of Brillio’s clients, a multimillion-dollar global real estate brokerage firm that oversees multiple brands and service businesses, faced challenges modernizing its systems. Established in the early 2000s, the rate of technological change has left it with software solutions in need of modernization. Additionally, many software development lifecycle choices no longer align with how the business has evolved over the past two decades.

As the firm continued to invest in technologies to drive its business, it maintained a small IT department. This team continued to deliver the desired outcomes to enable business growth. Still, it had become increasingly challenging as many systems required maintenance to ensure teams and partners could adapt to changing market, regulatory, and industry needs.

To optimize its IT systems, the firm turned to Brillio’s modernization toolset, BrillioOne.ai. The objective was to leverage AI to automate and augment the combined skills and resources available, thus achieving application modernization goals. According to the firm, “BrillioOne.ai added nimbleness to our software development. Adding an AI and automation solution helped accelerate the application scaffolding needed to drive business outcomes in our application modernization efforts.”

With BrillioOne.ai, the firm’s IT organization was able to leverage automation to change the software development cycle. With the help of AI, discovery, conversation, and testing were automated, and the DevOps teams, from both client and partner, could collaborate on exceptions rather than the mundane.

Modernizing applications provides the flexibility to leverage multicloud deployments

One of BrillioOne.ai’s assets is built-in support for multicloud deployments. As they develop modern software, enterprises must rely on multicloud environments to ensure flexibility, resilience, and cost efficiency. BrillioOne.ai provides the tools to support seamless deployment across various cloud platforms, including AWS, Google Cloud, and Microsoft Azure. Combining multi-cloud, AI, automation, and reporting allows Brillio’s clients to discover several long-term advantages, including:

1. Vendor independence: Mitigating the risks of lock-in and enabling negotiation leverage.
2. Enhanced disaster recovery: Distributing risk across multiple providers for improved business continuity.
3. Workload optimization: Matching specific workloads to the most suitable cloud environments for performance and cost benefits.
4. Global reach: Leveraging different cloud providers’ strengths in various geographic regions.

The Bottom Line: Enterprise IT leaders and their teams responsible for delivering applications modernization efforts must reimagine their SDLC with GenAI tools at the core.

Tools, people, and mindsets must evolve to become a Generative Enterprise™. For enterprises grappling with legacy systems and seeking to accelerate their digital transformation, BrillioOne.ai offers a comprehensive, AI-driven solution that modernizes applications, automates agile development, enhances digital engineering, and enables multicloud strategies. Brillio’s framework not only accelerates the pace of transformation but also mitigates risks by leveraging automation and enterprise-grade engineering capabilities.