How Apexon Is Building the Future of Responsible, Scalable Agentic AI

In conversation with Justin Marcucci, Chief Digital Officer at Apexon, the discussion unfolds around how enterprises can move beyond AI hype to meaningful, scalable transformation.

Artificial intelligence is reshaping how businesses operate, but the real question is no longer if companies should adopt it, but how they can scale it responsibly. In conversation with Justin Marcucci, Chief Digital Officer at Apexon, we explore how the company is helping enterprises move from experimentation to execution through its people-first, governance-led approach to Agentic AI.

Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon blends deep technology expertise with human intelligence to build AI systems that are transparent, secure, and sustainable. At the heart of this mission lies Agent Rise, the company’s proprietary Agentic AI platform, designed to deliver measurable business outcomes while maintaining compliance and trust.

India at the Core of Apexon’s Global Growth

Apexon’s foundation is unmistakably India-first. Over 80% of its 5,000-strong workforce is based across delivery hubs in Bangalore, Chennai, Pune, Hyderabad, and Ahmedabad, where the company continues to expand aggressively.

Marcucci emphasizes that this strategy is not just about scale, but also about capability building. “Our CEO, Sriniketh Chakravarthi, plans to double our India workforce to around 10,000 over the next four years,” he says. “We’re investing heavily in our people, because we’re only as strong as their ability to make smart technical decisions.”

Every Apexon associate receives 40–60 hours of AI-focused training annually, and over 80% of employees are already certified in GenAI. Collaborations with IIT Madras and Imperial College London strengthen Apexon’s research ecosystem. The company’s recognition as a Great Place to Work for nine consecutive years in India and six in the U.S. reflects its enduring commitment to a people-first ethos.

From Pilots to Platforms: The Rise of Agentic AI

Across industries, AI implementation has been hampered by messy data, unclear ROI, and limited scalability. Marcucci notes that 80% of Apexon’s client engagements now focus on AI, but many organizations are still in the early stages of readiness.

To bridge that gap, Apexon uses a two-track approach:

  1. Pilot programs that demonstrate tangible business outcomes and create early momentum.
  2. Architecture readiness initiatives that strengthen data and governance foundations for sustainable scaling.

This maturity framework inspired the creation of Agent Rise, a platform launched in mid-2024, designed to operationalize AI responsibly. Built around observability, explainability, and domain-specific governance, it helps organizations deploy AI solutions that can scale confidently across business functions.

“Every AI decision should be transparent about what it did, why it acted that way, and how it reached its conclusion,” says Marcucci.

Governance Before Growth

With global AI regulation still evolving, Apexon has made governance and observability central to its platform design. Agent Rise provides full traceability of AI agents’ actions, ensuring compliance and explainability from day one.

This is particularly crucial in industries such as banking, financial services, and healthcare, where data sensitivity is high and compliance is non-negotiable. Apexon’s experience with top-tier financial institutions has shaped a security-first architecture where data protection is built in, not bolted on.

Data as the Core Enabler of Transformation

Marcucci believes that no AI initiative can succeed without a strong data foundation. “Without solid data architecture, AI adoption simply can’t scale,” he asserts. Apexon’s work focuses on data preparation, governance, and workflow integration, helping clients transform raw, unstructured data into meaningful insights.

Recent success stories include:

  • A global automotive SaaS provider that achieved a 99% reduction in credential management efforts.
  • An investment bank that cut its audit cycle times by 70% through multi-agent orchestration.

These results demonstrate the effectiveness of well-governed, domain-specific AI in delivering measurable efficiency gains that far exceed proof-of-concept pilots.

Learning from the Most Regulated to Transform the Rest

Apexon’s strategy of mastering AI in the most demanding industries, such as life sciences and healthcare, allows it to apply the same rigor across less regulated sectors. In life sciences, for example, Apexon is building AI-driven control towers that predict delays in clinical trials by analyzing millions of data points.

“Once we refine these models in life sciences, we can easily adapt them for industries such as automotive or retail,” Marcucci explains. “If it works under the toughest regulations, it will work anywhere.”

Built-In Security and Data Resilience

As AI systems grow more complex, so do threats such as data poisoning and model manipulation. Apexon has embedded cybersecurity principles into every layer of its design. The Agent Rise platform was architected under the guidance of Mukund (Global Head of Data, Analytics & AI) and Umashankar Kotturu (Head of Digital Engineering), both seasoned experts in enterprise data security.

Their leadership ensures that Apexon’s AI implementations are not only intelligent but resilient,   an essential requirement for clients in BFSI and healthcare.

Partnering for the Long Term

Apexon’s business model is grounded in partnership, not transactions. “Ninety percent of our annual revenue comes from clients we’ve worked with before,” says Marcucci. “We’re not just implementing AI; we’re helping it evolve responsibly within each organization.”

By co-developing solutions and ensuring that outcomes align with investment, Apexon positions itself as a strategic AI partner focused on sustainable, measurable impact.

What’s Next for Enterprise AI

As enterprises shift from pilot programs to enterprise-wide AI deployment, Marcucci foresees responsible scaling as the defining challenge of the next 12–18 months. Governance, data quality, and explainability will separate leaders from laggards.

As India continues to serve as the epicenter of AI talent, Apexon’s model, combining upskilled engineers, robust governance, and transparent technology, may well become the blueprint for the next phase of global digital transformation.

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