TechStoriess sits down with Sanjay Sehgal, Founder, Chairman, and CEO of Aziro, a veteran technology leader with decades of experience building and scaling global engineering organisations. Sehgal has been at the forefront of enterprise product engineering, guiding companies through complex transformations across cloud, data, and AI-driven systems. His leadership has shaped Aziro into a partner for large enterprises tackling mission-critical modernisation challenges.
In this conversation, Sehgal cuts through the usual narrative and points to a deeper issue: most organisations still treat legacy modernisation as a technology upgrade instead of rethinking how their systems and business models actually work. He explains how this flawed approach leads to tightly coupled systems, rising change debt, and slow, high-risk progress.
The discussion also explores why enterprises favour modernisation over full rebuilds, and how AI-ready architectures and lifecycle-driven engineering are reshaping the future of software systems. Lets dive in to Q & A
What is fundamentally broken in legacy modernisation, and why it remains unresolved
From what we’ve seen at Aziro, legacy modernisation keeps stumbling for a simple reason, most organisations treat it like an IT upgrade instead of a full rethink of how the business runs. Teams start with tools and tech choices without first understanding domain boundaries or where value actually flows. The result? Systems that are tightly coupled, interfaces that break easily, and an architecture that’s impossible to evolve.
On top of that, companies tend to optimise for short‑term fixes, patches that keep things running but quietly pile up “change debt.” Add the shrinking talent pool for older technologies and the lack of a proper product mindset around core systems, and modernisation ends up stuck in a loop of delays, trade‑offs, and risk‑avoidance.
Until organisations shift their mindset from “upgrade the technology” to “redesign how the business systems should work,” legacy modernisation will continue to move slowly, carry risk, and deliver less value than expected.
Why enterprises choose to modernise instead of rebuild
Most large organisations pick modernisation because it lets them move forward without putting mission‑critical systems at risk. A full rebuild sounds exciting, but for industries that run 24/7, it’s a huge operational and regulatory gamble. Modernisation offers a safer, more gradual path: peel off domain capabilities, add APIs, improve the data plumbing, and introduce cloud capabilities step by step.
From what we see at Aziro, this approach protects institutional knowledge that would often disappear in a full rewrite. It also allows teams to keep systems running while steadily improving them.
The outcome is simple: organisations modernise their stack, release updates faster, and prepare for AI and future innovation without betting the entire business on a single, high-risk rebuild.
Rewrites still have a place, but in most cases, modernisation is the more stable and cost-effective path.
Why Aziro rebuilt its brand from scratch
The shift to Aziro from Msys was much more than adopting a new name. It marked a step forward with a clearer commitment to helping enterprises build intelligent, AI‑driven software ecosystems. As the company grew globally and deepened its product engineering capabilities, it became important for the brand to reflect that evolution. Aziro represents that shift.
Our clients trust us with some of their most ambitious transformation programs, and with AI now embedded deeply into our engineering DNA, the new identity strengthens that trust. The refreshed visual language and market narrative reaffirm the company’s long‑standing engineering ethos while signalling our ambition to drive cognitive automation, platform modernisation, and deep‑tech innovation. In many ways, Aziro is a statement of intent, a clear expression of who we are, what we solve, and how we partner with enterprises to design tomorrow’s opportunities.
How enterprise product engineering is shifting to lifecycle‑driven innovation
Enterprises are moving away from traditional “build once and release” models and adopting a continuous lifecycle approach where platforms evolve based on real usage, reliability targets, and business priorities. Product teams now work with ongoing roadmaps, performance objectives, and telemetry that guides decisions. Instead of running large, isolated projects, organisations invest in long‑lived teams that own outcomes like availability, security, and cost‑efficiency. Engineering decisions are supported by policy automation, reusable components, and better developer experiences that reduce time spent on repetitive tasks. Funding models are also changing, with budgets tied to outcomes rather than one‑time delivery. This shift helps enterprises modernise faster while maintaining stability and compliance.
Architectural changes required for AI‑ready enterprise systems
As enterprises embed AI throughout their software stack, they are rethinking architecture to ensure scalability, governance, and repeatability from the start. Modern designs focus on unified data layers, feature stores, and vector‑based search that allow models to learn and adapt reliably.
To support performance, organisations use event‑driven processing, GPU‑optimised clusters, and infrastructure that can flex with workload demands. Governance is becoming more sophisticated, with clear lineage, access controls, and automated policy checks across both training and inference. Observability now includes model drift, data quality, and safety indicators. These changes ensure that AI operates reliably in high‑stakes environments while remaining secure, compliant, and easy to scale.
Why Japan faces a modernisation crisis and how Aziro fits in
Japan’s modernisation challenge has reached a critical point, with METI’s “2025 Cliff” now becoming a reality for many enterprises. Core systems-built decades ago are still running essential operations, and the shortage of highly skilled engineers has made it increasingly difficult for companies to modernise these platforms on their own. The combination of aging systems, limited technical talent, and rising operational complexity has created a nationwide transformation bottleneck. Aziro’s entry into Japan is a direct response to this need. With deep AI-native engineering capabilities and global delivery centres, Aziro aims to help Japanese enterprises modernise legacy architectures, responsibly apply AI, and build scalable digital foundations that can support sustainable, long-term innovation.
How Aziro’s Japan model differs from traditional outsourcing
Aziro’s engagement model in Japan is designed very differently from conventional outsourcing approaches that tend to emphasise offshore delivery and cost efficiency. Our focus is on complementing Japan’s talent ecosystem with specialised global engineering capabilities that are difficult to hire domestically, particularly in AI, cloud, and data science.
Through a blend of local leadership, bilingual collaboration, and global engineering depth, we support modernisation, cognitive infrastructure, and large-scale digital programs with high reliability and transparency. Flexible models such as dedicated labs, ODCs, and specialist pod-based teams allow us to align closely with Japanese enterprises and SIers. The goal is not to replace local capability but to strengthen it, ensuring trust, continuity, and long-term transformation outcomes.
