Q: How is EPAM NEORIS positioned within the digital transformation ecosystem in Latin America?
A: We are a leading force in the region, specializing in software development, systems integration, cloud services, and artificial intelligence. A pivotal shift occurred recently when NEORIS was acquired by EPAM. Previously, EPAM already had a strong presence in Mexico and across Latin America, and with the addition of NEORIS, this presence has been further strengthened with regional clients. At the same time, EPAM continues to leverage its solid nearshore capabilities, serving clients in the United States and the European Union. This integration allows us to combine global engineering excellence with deep local market expertise. As EPAM NEORIS, we are now uniquely positioned to serve regional clients directly, leveraging a world-class portfolio to drive innovation across the Latin American market.
Q: Following the integration of capabilities between EPAM and NEORIS, what corporate decisions have been most decisive in establishing a differentiated value proposition?
A: The most strategic decision has been our evolution to become the dedicated Latin American division of EPAM, a process involving rigorous practice adoption and rebranding. By integrating EPAM’s highly mature methodologies, which have served global giants like Google, SAP, AWS and Microsoft, we have significantly expanded our service portfolio. For our clients in Mexico, this means access to a much broader and more sophisticated array of technological solutions. We are essentially bridging the gap between global elite engineering and regional business needs, providing a level of technical depth that is rare in the local market.
Q: Given the competition in IT services and consulting, how does ETAM NEORIS stand out?
A: Our competitive core rests on three pillars: engineering excellence, strategic alliances, and elite talent development. We leverage the high standards of software execution that made EPAM a global leader to satisfy the most demanding technological requirements. Furthermore, our deep-rooted relationships with major global technology providers allow us to pass significant strategic advantages directly to our clients. Finally, we maintain a highly competent pool of consultants and engineers through exceptionally rigorous hiring filters and continuous certification programs in emerging technologies, ensuring that our team remains the most skilled in a crowded marketplace.
Q: In an environment where clients demand measurable results, how do you structure your offering to translate technological capabilities into direct impact on business metrics?
A: We tackle AI adoption not as a series of individual efforts, but as a comprehensive value chain. We guide our clients through a program that optimizes every stage of the software development lifecycle, from requirement definition and user experience to coding, testing, and deployment. By identifying exactly where AI agents provide the most significant advantages, we can move beyond the hype and focus on systemic productivity.
We measure our impact by establishing clear Key Performance Indicators (KPIs) and baselines to demonstrate incremental benefits in productivity and development time reduction. Our analysis also accounts for hidden costs, such as the consumption of tokens in AI tools, to provide an accurate calculation of the real value generated. This transparent, data-driven methodology builds the necessary trust with our clients to scale these projects from initial proofs of concept to large-scale implementations that guarantee tangible business results.
Q: From a technological perspective, what distinguishes your native AI solutions from other market offerings in terms of scalability, personalization, and speed of implementation?
A: Our distinction lies in a multi-layered approach that addresses development, application embedding, and data governance. While we use AI to accelerate software production, we also specialize in embedding AI within applications so businesses can “talk” to their data in a conversational manner, similar to interacting with ChatGPT. However, for these tools to be effective, the underlying data must be clean, secure, and well-organized. That is why we provide the essential governance and “guardrails” to manage costs — preventing exponential spikes in token usage — and ensure that AI behavior remains within the specific safety and operational parameters required by the organization.
Q: What type of business problems do you solve through your Innovation Labs and what metrics are you using to validate these developments?
A: Our Innovation Labs proactively solve industry-specific challenges by merging digital and physical experiences. For example, we designed a seamless 360° journey for airline passengers, ensuring the interaction remains identical whether they are using a mobile app or speaking to a representative at the airport. In the healthcare sector, we developed a smart hospital room that integrates Internet of Things (IoT) telemetry and sensors with medical records. This solution automates the registration of vital signs and medication, allowing nurses and physicians to focus entirely on patient care rather than administrative paperwork.
Q: The Latin American market is accelerating its investment in Generative AI but still faces gaps in technological modernization. What operational or financial risks do companies assume when adopting AI without resolving their legacy systems?
A: Large enterprises with mature data management and security protocols can transition to AI relatively smoothly; however, SMEs face a significant risk if they do not close the data availability gap. Adopting AI tools while operating on fragmented legacy systems leads to inconsistent results and missed opportunities. Companies must launch modernization initiatives that prepare their data infrastructure simultaneously with their AI experimentation to ensure the technology has a solid foundation to act upon.
There is a critical “chain” consisting of applications, data, and AI that must be closed to achieve success. Often, the ability to utilize AI effectively requires updating the underlying application layer to ensure it generates consistent, high-quality data. Companies that attempt to bypass this fundamental step risk investing in expensive AI solutions that cannot produce reliable insights, ultimately resulting in a poor return on investment and operational frustration.
Q: Given that 70% of Chief Information Officers (CIOs) in the region plan to increase investment in AI and machine learning, are we witnessing strategic adoption or a phenomenon driven by competitive pressure?
A: We are seeing both, though the proportions vary. Strategic leaders view AI as a clear differentiator and are iterating to find the sweet spot where investment yields maximum value. Conversely, a large group of companies is moving into AI primarily due to a fear of missing out or competitive pressure. These organizations often face hurdles because AI requires a clear strategic purpose to justify the necessary investments in data and application restructuring; without a defined roadmap, they may be blindsided by exponential costs and a lack of measurable benefits.
Q: How is this wave of AI adoption affecting the talent landscape in Latin America, especially given the shortage of STEM skills and the need for hybrid profiles?
A: We can make some forecasts with certainty, but there is uncertainty in other areas. There is certainty that AI will always require a “human-in-the-loop” to validate outputs, eliminate hallucinations, and select the best generated code. While repetitive tasks may disappear, new roles will emerge, much like the shift seen during the Industrial Revolution or the move to serial manufacturing. The uncertainty lies in exactly which new titles will be created, but we know that the most valued skill in the near future will be adaptability.
Q: How do you foresee the evolution of the digital transformation model in the region over the next three to five years?
A: We anticipate a significant acceleration driven by the need to stay competitive through AI. However, this will create a unique tension. Companies must innovate aggressively while simultaneously navigating a volatile global economy and internal pressure to reduce costs. Digital transformation requires substantial investment, so the winners will be those who can balance this “efficiency versus innovation” paradox.
Q: What are EPAM NEORIS’ expansion priorities in Latin America in the short and medium term?
A: Our primary objective is to finalize our transition into the unified Latin American hub for EPAM, consolidating our footprint in Mexico and across South America. We are shifting from being a delivery center for foreign markets to becoming the partner of choice for local enterprises seeking high-end engineering. By scaling our AI governance frameworks and specialized innovation labs, we aim to lead the region’s digital acceleration, helping Mexican and Latin American firms achieve global levels of technical maturity and operational efficiency.