Speed, Scale & No Pilots: Arun Varadarajan on AAVA’s Transformative Edge

When 75% of enterprises use AI but only 26% scale it, something has to change.

Arun Varadarajan, Chief Commercial Officer at Ascendion, talks about how AAVA is reshaping enterprise SDLC with agentic AI. He shares how it automates the entire development journey — from ideation to deployment — while keeping human oversight at the core. Arun further touches on how AAVA bridges the gap between traditional IT setups and the agility enterprises need to scale AI meaningfully.

How does AAVA’s agentic AI streamline enterprise SDLC to deliver transformative outcomes?

At Ascendion, we've always believed software engineering isn't just about code. It's about accelerating transformation and impacting lives at scale. In a world where 75% of enterprises deploy AI but only 26% scale it, AAVA reimagines the entire SDLC by orchestrating agentic workflows that automate from ideation to operations. It blends over 4,000 AI agents with human oversight for seamless, efficient execution. Think of it as embedding digital co-workers into your processes. Agents handle dependency analysis, code generation, testing, and deployment autonomously, while humans validate and refine for precision.

Take a major U.S. healthcare leader, serving millions. Using AAVA, we migrated their legacy Hadoop platform to GCP in just 9 months at 70% lower cost. We automated over 85% of the process. This unlocked faster data processing for 4,000+ engineers and scientists, empowering better patient outcomes. The result? Cycle times slashed by 50%, defect detection up by 45%, and a scalable platform driving real business value. We're the anti-experiment partner. Our 32% POC-to-production conversion crushes industry benchmarks of 20-25%, with 80% of clients skipping pilots for direct wins. Looking ahead, AAVA positions enterprises to thrive in an agentic future where speed and efficiency aren't luxuries. They're essentials. This approach just earned us Leader status in the 2025 ISG Provider Lens™ for Generative AI Services in both Strategy & Consulting and Development & Deployment quadrants. 

What makes AAVA’s approach to legacy modernization a game-changer for enterprises, compared to traditional methods?

Traditional legacy modernization is often a nightmare. It's manual, error-prone, and dragged out over years with ballooning costs. AAVA flips the script by leveraging agentic AI to automate the heavy lifting. This makes it faster, cheaper, and far more reliable. We decompose legacy code into workflows where agents perform reverse engineering, dependency mapping, and forward design. All of this happens with human-in-the-loop for precision and co-ownership of outcomes.

For instance, for a leading home healthcare provider, we transformed their IT support process using AAVA. We drastically reduced downtime and enhanced patient care delivery. Unlike old-school methods that rely on scarce SMEs and outdated docs, AAVA handled complex integrations autonomously. It cut resolution times and operational friction. We've seen similar wins. A 40-year-old wealth management platform modernized at one-third the cost and half the time, from $36 million down to $9 million in 18 months. This isn't hype. It's pragmatic engineering that frees enterprises from legacy shackles. It enables innovation without the usual risks.

How does Ascendion bridge the gap between traditional IT firms and niche developer tools to drive enterprise software innovation?

Traditional IT firms promise the world but often deliver slideware. They're slow, rigid, and disconnected from real outcomes. Niche tools? They're great for devs but fall short on enterprise scale. They lack integration and governance. At Ascendion, we bridge this gap with AAVA, our low-code/no-code agentic platform boasting over 4,000 agents and 300+ workflows. It orchestrates end-to-end SDLC, combining robust services with AI-powered agility in a way that's bold, boutique, and outcome-obsessed.

Consider a high-growth client in gaming or tech, with a global reach for millions of users. We accelerated their product launch from 21 months to 10 months, using AAVA to automate design, build, and deployment. This boosted revenue and valuation. The co-engineering model gives clients full access to customize agents in their environments. It's unlike siloed tools. We've driven $1 billion in projected savings for a global tech enterprise through pilots that set benchmarks in velocity and quality, with 70% agent reusability. Bluntly, we're not just vendors. We're partners engineering the future, where innovation scales enterprise-wide. We're the sweet spot for turning AI experiments into scaled impact.

How does AAVA address enterprise concerns about agentic AI, such as security and governance, to deliver trusted solutions?

Enterprises rightly worry about agentic AI. Security breaches, compliance slips, and unchecked autonomy can be disastrous. But AAVA is built with trust at its core. It's SOC 2 compliant, with baked-in guardrails like real-time monitoring, audit trails, and evolving AI oversight that learns exponentially. This goes far beyond static human checks.

We've proven this in regulated sectors. For a top global bank, AAVA transformed customer service. It saved $20 million immediately while adhering to strict data protocols. There were no leaks and full transparency. Agents operate in client-controlled environments. They integrate via APIs and MCP for seamless, secure coordination. And unlike humans, who fatigue, AI agents maintain consistent governance. They reduce errors by up to 60% in the cost of quality. Forward-thinking, AAVA isn't just safe; it's a foundation for ethical AI that turns concerns into competitive edges. With our 32% POC-to-production rate and 80% of clients jumping straight to transformations, we're co-owning outcomes that build confidence.

What SDLC inefficiencies does AAVA eliminate with its agentic AI, and how does it outperform SaaS/low-code platforms?

SDLC friction points like manual handoffs, rework, and silos waste time and money. AAVA eliminates them with agentic workflows that automate 90%+ of tasks. This covers everything from epics to deployment. It slashes cycle times by 50% and boosts defect detection by 45%. 

SaaS/low-code platforms? They're rigid, with high customization costs and IP lock-in. AAVA outperforms by being interoperable. It has plugins for Jira, GitHub, and ServiceNow. It's tailored to your standards without vendor traps. For a major shipping provider handling billions of packages, we delivered 40% faster cycles. That's far beyond generic SaaS. It's outcome-based. Pay for impact, not access. In essence, AAVA turns inefficiency into velocity. It outpaces others with enterprise-grade scalability and reusability up to 70%. As the anti-experiment partner crushing benchmarks with 32% conversions, we're positioning you for $2M+ annual savings, like our F500 wins.

What’s a common CTO misconception about agentic AI development, and how does AAVA reframe it for enterprise success?

A big misconception? That agentic AI spits out "crap code." It's unreliable, untested junk that creates more problems than it solves. CTOs fear it lacks rigor. But that's outdated thinking from early GenAI hype.

AAVA reframes this with audited, standardized outputs. Agents follow your coding standards, patterns, and best practices. They generate production-ready code that's battle-tested. For a global consultancy, we modernized legacy systems for healthcare and education. We accelerated transformation with clean, compliant artifacts serving 600,000+ researchers. It's not magic. It's engineering. Workflows with human-in-the-loop ensure quality. They reduce rework by 60%. Reframed, agentic AI is a superpower for success. It empowers CTOs to innovate confidently. With our boutique edge and metrics like 50% velocity gains, we're the reason 80% of clients skip pilots.

What emerging SDLC metrics will matter by 2030, and how does AAVA position enterprises for this agentic AI-driven future?

By 2030, SDLC metrics will shift from velocity and defects to agentic ones. Digital Work Quotient (DWQ), measuring AI contribution, reusability rates (aiming 70%+), and ROI on autonomy. This means tracking how agents amplify human output.

AAVA positions you there today, with metrics like 30-40% velocity gains and real-time optics via OneView. For a sports tech leader serving 54 million athletes, we built scalable platforms with these forward metrics in mind. It's about outcomes. $1 billion savings roadmaps, faster launches. AAVA isn't just a tool. It's your playbook for an agentic era, where enterprises lead through AI-human synergy. As a $600M+ revenue powerhouse with 32% POC conversions, we're co-owning transformations that surge pipelines 55% ahead. We are really excited about AAVA, our solution for an agentic AI-driven future. Combined with Ascendion's engineers and our human-in-the-loop approach, it is a leader in agentic AI for the full SDLC in enterprises.