AI Redefines the Rules of Data Assurance, Maneesh Jhawar, Founder and CEO, QualityKiosk Technologies

By Puja Sharma

QualityKiosk is putting AI at the heart of digital assurance, turning reliability from a reactive checkpoint into a proactive driver of trust in FinTech

How is AI transforming digital assurance?

As enterprises accelerate their digital assurance transformation, the focus is centred on three critical dimensions of applications, data, and program assurance. AI is now redefining how assurance
is delivered across all three, and importantly, it is doing so with unprecedented speed and intelligence.

Take applications, for example. By leveraging sub-domain trained models, AI can now generate continuous intelligence, drawing from usage history and production incidents, to dynamically optimise the checks needed. This means assurance is no longer static; it adapts in real time, identifying exactly what to validate, and when, based on areas most vulnerable to risk.

While AI is already transforming how digital assurance is being done at an application level, the real breakthrough lies in how it is redefining data assurance. We are at a unique inflection point where AI is no longer just supporting execution but actively shaping the strategy and operating model for ensuring trusted data.

For program assurance, AI has become the backbone of intelligent decision-making. Beyond validation, AI is now curating data in context, aligning it with real-world usage patterns and business
needs, ensuring quality where and when it matters most. Routine activities are being autonomously managed by agentic bots, ensuring hygiene and compliance, while AI-driven platforms provide business leaders with contextual insights that guide smarter investment and prioritisation choices.

Agentic AI bots are addressing long-standing challenges around accuracy and adequacy, drastically compressing the time required for assurance, and elevating confidence in outcomes. This shift is ushering in a new era of intelligence-driven assurance, where decisions are guided not just by compliance requirements, but by dynamic, usage-based insights that ensure reliability at scale.

At QualityKiosk, we are proud to be at the forefront of this shift. We are partnering with large and mid-sized enterprises to put AI at the centre of their assurance journey, transforming reliability from a reactive measure into a proactive, business-critical outcome. Our customers are already realising the impact of this change: faster delivery, higher confidence, and greater trust in every digital experience.

With enterprises shifting to multi-cloud and cloud-native setups, how does QualityKiosk ensure performance, reliability, and seamless user experience across distributed systems?

In a multi-cloud environment, resiliency is the cornerstone of success. At QualityKiosk, we are committed to engineering reliability into every stage of development. By emphasising Shift-Left practices, we increase Mean Time Between Failures (MTBF) while reducing Mean Time to Resolve (MTTR), ensuring issues are prevented before they surface and resolved faster when they do.

AI plays a pivotal role in this journey. Our AI-led observability framework eliminates blind spots, autonomously triages insights, and enables proactive interventions to maintain operations with near zero critical incidents. This means our clients’ systems remain not just functional, but truly dependable.

Equally important, we place end-user experience at the heart of assurance. It is the ultimate validation of our strategies, providing real-world usage insights that continuously refine our approach and further extend MTBF.

By harnessing AI’s ability to process massive volumes of observability data, we can filter out noise and surface actionable insights in real time. At the same time, AI helps us understand user behaviour patterns, identify potential vulnerabilities, and provide business leaders with clear visibility into ROI, empowering smarter, data backed investment decisions.

Our mission is clear: to combine reliability engineering excellence with AI-driven intelligence, ensuring resilience, reliability, and trust in every digital interaction.

With digital banking under regulatory and customer scrutiny, how is QualityKiosk enabling financial institutions to deliver consistent, zero defect experiences?

In a regulated industry like banking, delivering reliable, zero-defect software isn’t a nice-to-have; it’s the baseline. When you’re dealing with monetary transactions, there’s simply no room for error. That’s why our focus has always been on shifting left, injecting quality as early as possible in the development cycle. Building reliability starts with assuring requirement quality, and extends to maintaining uncompromising control over code, data, integrations, and environments, creating a foundation of trust, compliance, and resilience.

Unlike other industries where teams can experiment in production and iterate, banks don’t have that luxury. Reliability must be proven in lower environments before anything reaches production. And equally important, teams need a deep understanding of regulatory requirements: compliance can’t be an afterthought.

This is where we see the real opportunity: institutionalising regulatory and domain knowledge into a RAG-powered data store. We’ve leveraged our 25 years of experience in banking and
insurance to integrate it into our AI platform, enabling our clients to achieve repeatable, predictable results while staying ahead of both compliance and customer expectations.

How do AI platforms like DevRev and Katalon accelerate QualityKiosk’s mission to deliver faster innovation and better customer experiences?

We see reliability not as a box to tick at the end of a project, but as something that needs to be baked into the DNA of an organisation. That’s exactly what our partnerships with DevRev and Katalon are helping us achieve: making quality and consistency part of every release, so companies can build trust at scale while reducing risk and manual effort.

With DevRev, we’re turning our domain knowledge into autonomous reasoning agents that work across the entire software testing lifecycle. Think of our CX agents as smart copilots—they analyse customer journeys, market sentiment, test outputs, and even support tickets to help teams prioritise engineering tasks, improve coverage, and cut down on production issues. Meanwhile, our failure analysis agents keep a constant eye on what’s failing, how often, and what’s likely to fail next—giving engineering teams clear direction on where to focus.

On the innovation side, we’re combining QK’s domain strengths with DevRev’s AgentOS and knowledge graph to create agents that are not just conversational but execution ready. And because we’re DevRev’s platinum partner, we can roll these out in as little as two weeks, while also managing ongoing agent operations and providing quality engineering for AI validation.

Katalon, on the other hand, helps us take automation to the next level. We use its unified platform alongside our frameworks and domain repositories to deliver true end-to-end test automation.
As their launch partner for TrueTest, we’re breaking new ground by automatically creating test scripts from user journey heat maps. On top of that, our close work with Katalon’s product engineering and testing teams gives us an insider’s edge, which we pass directly to our clients.

Together, these partnerships are helping us redefine reliability for the AI era, making us smarter, faster, and more proactive and inspiring confidence and trust with every release.