To see how the two-pronged approach works in practice, here are a few success stories from enterprise deployments.

Global professional association – AI assistants at scale

A leading global non-profit professional association with a community of over 2.9 million professionals collaborated with us to deploy AI assistants for project management professionals. Our model assurance approach achieved 99.4% accuracy using:

Automated ground truth generation
Automated LLM evaluations
Topic modeling

Originally launched as a genAI pilot in the early days of adoption, the platform has now evolved into a SWARM (scalable, workflow-driven, autonomous, role-based multi-agent) agentic architecture, with an expanded target audience spanning enterprises and individual users. This scale demanded rigorous assurance across agent hand-offs, multi-tool access, and top-k response validation.

Model assurance spanned the entire lifecycle—from data preparation and input validation to process and output validation. We leveraged synthetic Q&A data generation pipelines, LangChain-based evaluation metrics, ground-truth accelerators, and Judge LLMs to assess custom metrics such as answer relevance, contextual grounding, and content prioritization.

Responsible AI dimensions, including guardrails, bias, prompt injection, and negative scenario testing, were implemented using the retrieval augmented generation assessment system (RAGAS) 2.0 framework and custom bidirectional encoder representations from transformers (BERT) models. With high levels of automated coverage, the program progressed from 70% accuracy in pilot to 99.4% at general availability, delivering an 80% reduction in manual testing effort.

Global healthcare insurer – genAI-powered benefit inquiry

For a global healthcare insurer, we helped build and deploy a genAI-powered benefit inquiry system supporting human agents. The solution was validated end-to-end using our internal model assurance framework and accelerators.

The business impact included a 30% reduction in manual effort and successful scaling to 10,000+ clients.

Conclusion

The Bank of America Global Research predicts that the total addressable market for agentic AI will reach $155 billion by 2030. At the same time, enterprises are facing increasing POC fatigue, with many struggling to scale genAI pilots into production with confidence. As McKinsey aptly notes, “AI agents offer a way out of the genAI paradox.”

Scaling enterprise genAI successfully requires more than innovation—it demands an assembly-line approach to assurance, with built-in testing, evaluation, responsible AI guardrails, and continuous validation. A trusted partner like Virtusa enables organizations to industrialize AI adoption with confidence, ensuring that AI systems are not only powerful but also reliable, safe, and enterprise-ready.

Note:

Tom Coshow, Senior Director Analyst, “Intelligent Agents in AI Really Can Work Alone. Here’s How.”, Gartner, October 1, 2024 https://www.gartner.com/en/articles/intelligent-agent-in-ai
Diego Lo Giudice, VP & Principal Analyst, “The Next Generation of Modern Software Development Is Here: Embrace It Or Die”, Forrester Research, Inc., July 17, 2023
https://www.forrester.com/blogs/the-next-generation-of-modern-software-development-is-here/
McKinsey & Company / QuantumBlack, “Seizing the Agentic AI Advantage”, June 13, 2025
https://www.mckinsey.com/capabilities/quantumblack/our-insights/seizing-the-agentic-ai-advantage

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