Author: Malavika Madgula

Imagine a bank that runs pre-runtime security before opening: this includes installing cameras, locking doors, and hiring and training staff and employees. This is basically the testing bit of securing an AI (artificial intelligence) model before deployment. Next, there’s runtime security, which takes place during working hours, when customers walk in and interact with tellers and transactions take place. Now here come the glitches: someone trying to move money illegally, behaving suspiciously, or trying to pass a fake cheque. This is where surveillance systems and live security guards step in, stopping threats immediately by detecting unusual activity and monitoring behaviour…

In an era where capital is moving faster than cognition, the convergence of machine precision and human strategy is no longer theoretical— it’s the very architecture of survival. According to a February 2024 report by the Alternative Investment Management Association (AIMA), a whopping 86% of the surveyed hedge fund managers allowed some employees access to multiple Generative artificial intelligence (GenAI) tools to support their work. That number was up to 95% by September 2025. Hedge funds, especially multi-strategy ones, are already deploying fleets of artificial intelligence agents (AI agents) to expand stock coverage and research capacity dramatically, and we could…

A new-age, open-source hedge fund has 18 portfolio managers instead of one. Not only do they go beyond analysing stocks, but each one of them follows a different style, arguing, challenging each other, and even voting on what to buy or sell Oh — and they aren’t humans. It might not be managing money yet, but it’s already a reality of how AI (artificial intelligence) is now reshaping the way even trading decisions are made. Hedge funds and portfolio managers are now increasingly turning to AI and automation to modernise trading operations, even as data volumes explode, markets become more…

Imagine running a SaaS (Software-as-a-Service) platform where hundreds of businesses, from Fortune 500 firms to small bakeries, use an application simultaneously, with each of them expecting their performance to be unaffected by others and their data to be completely private This is exactly the kind of everyday reality that multi-tenant cloud architecture is designed to handle — many isolated worlds, a shared infrastructure. Multi-tenant cloud architecture is a cloud computing model where many tenants share the same infrastructure but maintain data security and isolation. This model not only ensures streamlined management, but also cost savings and efficient utilisation of resources.…

For nearly two decades, SaaS (Software-as-a-Service) pricing has worked like a well-oiled machine… In the cloud era, seat-based tiers and flat-rate plans made up for predictable MRR (monthly recurring revenue), with the value scaling with the number of users accessing shared systems. However, the traditional SaaS playbook was designed for a different era, where it made sense to tie value to access when it was users who were driving outcomes. In the AI (artificial intelligence) era, value has shifted from users to the work that the software performs on your behalf, automating tasks and deciding, analysing, and resolving on its…

On March 11th, 2026, the controversial mobile-first cryptocurrency, Pi, the native coin of the Pi Network, defied all market trends to surge 6%, outperforming the broader cryptocurrency market that day… This upward rally comes amidst a flurry of news: large wallet investors expanding their Pi holdings, consistent outflows from exchanges, a potential big-ticket listing, some positive pieces of news, and, of course, the onset of Pi Day on March 14th, 2026. In fact, the Pi token has been showing growing demand ahead of Pi Day, when the entire community celebrates the day corresponding to the mathematical constant Pi’s first three…

Get this: it’s the day before a family member’s birthday celebrations, and you desperately need a gift under USD 100 that arrives tomorrow… Instead of rifling across multiple tabs, you simply ask an AI assistant and bam – it understands your needs, evaluates the context and constraints, and recommends a gift choice you feel good about giving. Now imagine having such a personal AI assistant shopper in your lives – someone who deeply understands your budget, lifestyle, and preferences and effortlessly curates tailored product recommendations from thousands of choices, even getting you the best prices and completing transactions autonomously. Suddenly,…

According to a Katonic AI report, data triangulated from Gartner, IDC, and Forrester showed that Cloud spends grew from less than USD 20 billion in 2010 to a whopping USD 400 billion in 2024 – in a mere span of 15 years. According to new analysis, Agentic AI could follow an even steeper curve. A handful of hyperscalers hold an overwhelming majority of the market share today, but an emerging architectural pattern could shift the balance of power from these Cloud giants to intelligent agents, commoditising the very services that built their empires. This paradigm shift is driven by Generative…

The Indian technological space has been blowing up in February 2026, even as the India AI Impact Summit 2026 was underway in New Delhi. The reason? The unveiling of new indigenous and sovereign AI models from Sarvam, Gnani.ai, and BharatGen. Spanning real-world, voice, and language interfaces, these models are a huge step towards building homegrown alternatives to global AI systems dominated by Big Tech. Their launch signals a shift from being a user of global artificial intelligence tools to designing, building, and using domestic AI infrastructure aimed at education, healthcare, agriculture, and government services at population scale. Part of the…

The rapid rise and evolution of AI (artificial intelligence) have resulted in industries critically re-evaluating power-intensive servers supporting this technological surge Data centres are at the centre of this storm, as they’re critical to the infrastructure of the internet, consuming huge amounts of water and energy. Their biggest criticism is the fact that they’re burdensome to local resources and communities – besides being unsightly, of course. And as the demands for AI workloads increase, the strain on energy resources will escalate. In fact, we are probably racing towards a ‘tipping point’ where current data centre architectures aren’t viable. Case in…