As artificial intelligence continues to dominate conversations across industries, many startups are racing to introduce AI-powered features and automation tools. But according to Akash Chandra, the real opportunity in AI lies far beyond flashy demos or trend-driven innovation.

Through InsightAI, Akash is focused on solving a far more practical challenge  helping businesses make smarter, faster, and safer decisions using intelligent systems built around trust, explainability, and real operational impact.

In this email interview, Akash Chandra shares his journey into AI, the problem that led to the creation of InsightAI, and why he believes the future of enterprise AI will be shaped by practical intelligence rather than hype. 

“AI felt like the natural next step”

Before founding InsightAI, Akash spent years working around fintech and credit systems, where he was exposed to large-scale operational and risk-management challenges.

He explains that what initially attracted him toward AI was the complexity of the problems traditional systems struggled to solve.

“I was always interested in solving difficult problems where data was too complex for traditional systems,” he says.“While working in fintech and credit systems, I saw how much valuable information businesses had but were unable to use effectively.”

For him, AI represented something more meaningful than automation. It offered the ability to understand patterns, context, and risk at a much deeper level  something conventional systems were not designed for. 

The inefficiency that inspired InsightAI

The idea behind InsightAI emerged from a recurring pattern Akash noticed across enterprises.

Teams were spending enormous amounts of time manually reviewing transactions, documents, compliance workflows, and risk indicators. Despite organizations having access to large volumes of data, decision-making remained slow and reactive.

At the same time, fraud and security threats were becoming increasingly sophisticated.

“That gap between data availability and actionable intelligence made us feel there was a strong need for InsightAI,” he explains.

This realization eventually became the foundation for the company’s mission: building AI systems that help businesses convert complex information into practical intelligence.

Building AI that businesses can actually trust

Akash believes one of the biggest problems in the AI ecosystem today is the growing obsession with hype-driven features.

While many companies focus on creating AI products that look impressive in demonstrations, InsightAI chose a different direction from the beginning.

“We decided early that we did not want to build AI for demonstrations,” he says. “We wanted AI that businesses would rely on daily.”

For InsightAI, long-term value is not measured by novelty, but by measurable impact reducing risk, improving decision-making, and helping organizations save time in critical workflows.

This is also why the company places strong emphasis on explainability, security, and reliability rather than treating AI as a black-box technology.

What InsightAI does

For someone hearing about the company for the first time, Akash describes InsightAI in simple terms:

“InsightAI helps businesses make smarter and safer decisions using AI.”

The company works across areas such as fraud prevention, financial crime detection, risk intelligence, and document analysis.

Its broader mission is centered on helping organizations turn complex datasets into useful intelligence while making trust and security a built-in part of the process.

The misconceptions around AI adoption

Despite the rapid adoption of AI across industries, Akash believes many businesses still misunderstand how AI actually works.

“One common misconception is that AI is a magic tool that immediately solves every problem,” he says.

According to him, AI systems are only as effective as the data, workflows, and business context surrounding them.

Another common misunderstanding is the fear that AI completely replaces human roles. In reality, Akash believes the strongest systems are those where AI works alongside human expertise rather than replacing it entirely.

Why production AI is different from AI demos

Akash draws a clear distinction between systems that perform well in demos and systems that survive in production environments.

“Demos usually focus on showing best-case outcomes,” he explains, “while production systems have to deal with real-world challenges like scale, latency, errors, security, and changing data patterns.”

Because of this, InsightAI evaluates success through long-term reliability, consistent accuracy, customer feedback, and measurable business outcomes, not just short-term performance.

Earning trust in high-stakes environments

One of the biggest early challenges for InsightAI was convincing businesses to trust AI-driven systems, especially in areas involving compliance and fraud detection.

“In areas like fraud and compliance, people cannot rely on black-box outputs,” Akash says.

Businesses wanted transparency and context behind AI-generated decisions.

To solve this, the company invested heavily in explainability and contextual reasoning, ensuring users could understand not only what decision was made, but why it was made.

Balancing innovation with responsibility

In a rapidly evolving industry like AI, speed is often treated as a competitive advantage. But Akash believes responsibility matters even more.

“Speed matters because AI changes very quickly, but trust matters even more,” he says.

While the company moves quickly during experimentation, production deployment follows a much more disciplined approach involving extensive testing, continuous feedback, and rigorous validation.

In sectors involving security and financial decisions, he believes accuracy can never be sacrificed for speed.

The moment InsightAI felt truly impactful

One of the company’s defining moments came when investigators and risk teams shared how the platform had significantly reduced the time required for repetitive analysis work.

Tasks that once took hours could now be completed much faster and with stronger contextual understanding.

“When people say the system reduced effort and helped them focus on meaningful decisions instead of repetitive work, it becomes clear that the impact goes beyond technology,” Akash says.

The biggest lesson from building in AI

Reflecting on his journey, Akash says one of his biggest learnings has been understanding that technology evolves much faster than business problems.

“Models, tools, and frameworks keep evolving, but real customer pain points remain surprisingly consistent,” he explains.

This realization changed his perspective on innovation. Instead of chasing every new trend, he believes founders should focus on deeply understanding the problems they are solving.

What makes a company truly AI-first

According to Akash, there is a major difference between companies that are genuinely AI-first and those that simply add AI as a feature.

“AI-first companies design workflows, products, and decisions around intelligence from the beginning,” he says.

In those companies, AI becomes part of the foundation rather than an additional layer placed on top of existing systems.

The future of enterprise AI

Looking ahead, Akash believes enterprise AI will evolve far beyond content generation and simple assistants.

Over the next few years, he expects businesses to increasingly adopt AI agents and intelligent systems capable of handling larger workflows, monitoring risk, improving security, and automating repetitive operations.

At the same time, he believes humans will continue to remain an essential part of the loop.

Why Indian founders have a global advantage

Akash also believes Indian AI startups are uniquely positioned to compete globally.

“Indian founders are used to building under constraints and solving problems at scale,” he says.

According to him, the ability to work with complexity, cost sensitivity, and diverse user needs often pushes Indian startups to create highly practical and scalable solutions.

Fundraising and the importance of real outcomes

Speaking about fundraising, Akash says early investor conversations taught him an important lesson: strong technology alone is not enough.

While investors were excited about AI, they also wanted clear evidence of customer value, market demand, and long-term sustainability.

That experience reinforced the importance of balancing innovation with practical business outcomes.

Staying adaptable in a fast-moving industry

Building in AI can often become mentally exhausting because of the pace at which the industry evolves.

To stay grounded, Akash avoids chasing every new trend and instead focuses on continuous learning while staying closely connected to customer problems.

Outside work, maintaining routine, exercise, and occasional breaks helps him maintain balance and sustainability.

A belief that changed over time

Looking back, Akash admits that one of his earliest assumptions eventually changed.

“Initially, I believed the strongest technology would automatically win,” he says.

Over time, he realized that adoption, user experience, trust, and solving a specific problem are just as important as the underlying technology itself.

What excites him about the future

At present, InsightAI is particularly excited about systems that combine AI with graph intelligence and long-term contextual understanding.

The company sees major potential in areas like fraud detection, security intelligence, and AI agents capable of reasoning across both structured and unstructured information.

Advice for young AI founders

For founders entering the AI space today, Akash offers simple but important advice:

“Focus on the problem before the technology.”

He believes AI tools and trends will continue to evolve rapidly, but the fundamentals of building successful companies will remain the same, creating value, building trust, and understanding customer needs deeply.

Final Thoughts

The conversation with Akash Chandra reflects a broader shift happening in the AI ecosystem today. As the industry moves beyond hype cycles, companies like InsightAI are focusing on building systems that are not only intelligent, but also dependable, explainable, and deeply aligned with real business needs.

For Akash, the future of AI is not about replacing people, it is about helping people make better decisions in increasingly complex environments.

Interview By : Kashish Srivastava