Geek Chronicles Issue 10: From Fintech Floors to Studio Tables, Architecture and Clarity as Method
Geek Chronicles Issue 10 presents a collection of reports, field notes, and event reflections that document a month of work across technology, design, strategy, and culture at GeekyAnts. The issue brings together insights from Global FinTech Fest 2025, updates from engineering and analysis teams, coverage of partnerships and sales activity, and stories from colleagues across the organisation. It also includes cultural highlights such as the Diwali celebration, offering a grounded view of the company’s current rhythm.
Geek Chronicles Issue 10: From Fintech Floors to Studio Tables, Architecture and Clarity as Method
Wealth in the Metaverse
Between 2020 and 2022, an estimated USD 120 billion flowed into metaverse ventures, positioning virtual worlds not merely as experiments but as the next frontier of capital. Investors and brands rallied behind the idea that scarcity could be engineered in code and attention could be monetised indefinitely. What was once the domain of gaming and social spaces became reimagined as real estate, luxury, and identity. In that moment, the metaverse was not an escape but a thought experiment in turning belief into property.
By early 2024, the reality had shifted. NFT trading volume in Q1 hovered around USD 3.9 billion, roughly a third of what it had been at its speculative peak. Market contraction exposed the limits of belief-based value, especially when tied to proprietary platforms whose persistence depended on corporate incentives. The central question now is whether virtual wealth can survive beyond hype — whether the fantasy of value unbound from reality can mature into infrastructure that endures.
The Speculative Ascent
The first generation of virtual economies showed that imagination could have a market price. In 2006, Second Life produced its first real-world millionaire when Anshe Chung, the avatar of Ailin Graef, turned a ten-dollar deposit into over a million by buying and developing virtual land. The model mirrored real estate, with leases, tenants, and appreciation. It revealed not the novelty of digital space but the human impulse to treat presence as a scarce resource. The platform’s currency exchange and banking system foreshadowed the architecture that would later define blockchain economies.
The next shift came with NFTs in 2017. The ERC-721 standard made digital uniqueness programmable. Games like CryptoKitties proved that scarcity could be coded, and the thrill of ownership could drive demand. By 2021, this logic reached new extremes. Beeple’s Everydays: The First 5000 Days sold for USD 69.3 million at Christie’s, placing a digital file alongside fine art. Virtual land prices followed—parcels in Decentraland sold for USD 2.4 million, and estates in The Sandbox exceeded USD 4 million. Each sale blurred the line between speculation and legitimacy.
Institutional capital soon arrived. In late 2021, Facebook’s rebrand as Meta turned the metaverse from a subculture to a corporate vision. McKinsey estimated global investment at USD 120 billion within two years, as brands and financial firms built virtual storefronts, galleries, and branches. The ascent of the metaverse was less technological than social—a collective experiment in turning belief into balance sheet. At its height, it promised an economy where attention itself could serve as collateral.
By early 2022, the fantasy reached full inflation. Analysts projected trillion-dollar valuations, land scarcity inside servers became headline news, and venture firms described digital plots as the “Manhattan of Web3.” The infrastructure lagged behind the story. User activity remained thin, interoperability was absent, and most projects relied on unstable crypto liquidity. The rise exposed both the scale of human imagination and its limits: value expanded faster than the systems built to sustain it.
Collapse and Correction
By mid-2022, the network of NFT markets and metaverse tokens began to collapse under its own weight. NFT trading volumes fell by ninety-seven percent from their January peak of seventeen billion dollars to under five hundred million by September. The value of tokens such as MANA and SAND dropped by more than eighty percent, and virtual land prices followed. Daily traffic in worlds like Decentraland and The Sandbox dwindled to a few thousand users, far below investor forecasts. The promise of digital prosperity was revealed as a liquidity illusion, sustained more by speculative capital than real activity.
The collapse exposed structural flaws long embedded in the system. Ownership was never fully decentralised; most assets depended on proprietary servers and corporate governance. Interoperability was minimal, and valuations relied on token liquidity rather than user demand. When the broader crypto market imploded, these weaknesses deepened the shock. The fall of Terra and Luna wiped out sixty billion dollars, draining liquidity from NFT markets and freezing virtual-land assets. Projects like Axie Infinity, once models of play-to-earn success, lost ninety-five percent of their token value within months.
The downturn became a stress test for digital ownership. The ventures that endured were those with tangible utility: art registries preserving provenance, industrial digital twins delivering outcomes, and token standards improving transparency. Analysts called it a purification phase—a correction that stripped away speculation without halting innovation. What remained was smaller but more coherent, a foundation where digital wealth had to prove endurance rather than promise growth.
The New Utility Economy
By 2024, digital-asset markets began to recover on a smaller, steadier foundation. NFT trading volumes rose to nearly nine hundred million dollars in December, marking five straight months of growth. The momentum came not from speculation but from integration into functional systems. NFTs evolved into access keys, credentials, and proofs of ownership within hybrid digital–physical services. Real-world asset tokenisation accelerated as institutions explored fractional ownership of real estate, art, and carbon credits. PwC analysts projected the market could reach several trillion dollars within a decade, signalling that digital property had become a new layer of financial infrastructure rather than a novelty.
This change in orientation was reinforced by corporate adoption. Brands that once used NFTs as marketing tools began embedding them in product strategy. Nike and Gucci launched persistent digital lines, Disney tied virtual collectables to film franchises, and Apple approved NFT commerce within its App Store. In industry, Siemens and BMW used digital twins in NVIDIA’s Omniverse to simulate manufacturing and logistics. The metaverse was evolving from spectacle to operational tool, with value measured in utility and continuity instead of scarcity.
The idea of digital wealth matured in parallel. Ethereum retained about seventy percent of NFT trading volume, supported by standards like ERC-721 and ERC-1155. Legal systems began recognising NFTs as transferable assets, and regulators established taxation and reporting norms. Forecasts projected the metaverse NFT market to grow from three hundred thirty million dollars in 2023 to three billion by 2033. The new economy no longer promised instant riches but offered something more durable — ownership defined by use, governance, and persistence rather than hype.
The Moral and Institutional Frame
As the speculative phase faded, regulation replaced narrative as the stabilising force of the digital economy. Governments and financial institutions began defining ownership when value existed only as code. The European Union and Singapore classified certain NFTs as financial instruments, while South Korea’s Metaverse Promotion Act formalised data rights and consumer protection. Japan created a Web3 Strategy Office to promote interoperability, and the IFRS Foundation proposed accounting standards for virtual assets. Major consultancies introduced valuation methods for digital property. Together, these steps marked a shift from invention to institution: digital wealth now required governance, reporting, and audit.
This maturity reintroduced a moral dimension to virtual wealth. The early metaverse imagined freedom from physical and legal limits, yet its survival now depends on liability, disclosure, and stewardship. As custodial services, estate laws, and taxation frameworks absorbed digital assets, the gap between creativity and accountability narrowed. The fantasy of unbound value was turning into a system of shared responsibility, where legitimacy rested on transparency. The metaverse, once an emblem of escape, was learning to coexist with the order it had sought to transcend.
The Settlement Layer
The metaverse began as an experiment in abstract value and ended as a study in endurance. The early cycles of speculation left behind a network of ledgers, standards, and registries that now serve practical functions in art, industry, and commerce. Digital property became measurable through use and accountability rather than novelty. Each stage of its evolution traced the same question in new forms—how belief becomes infrastructure and how code begins to represent trust.
Virtual wealth now belongs to the architecture of finance. It connects to law, taxation, and custody; it interacts with markets that expect permanence. The fantasy that once animated its rise has settled into process and policy, yet traces of imagination remain within those systems. What was once an escape has turned into a continuity, where the persistence of value is maintained by shared rules instead of speculation. In that persistence, the idea of the metaverse finds its maturity.
Modernising the Core: How Fintech Leaders Are Thinking About AI
At the Global FinTech Fest 2025, Kunal Kumar, Chief Operating Officer at GeekyAnts, and Rakesh Ningthoujam, Head of Growth Marketing, stepped aside from the flow of scheduled sessions to talk about what they were hearing from enterprises visiting the GeekyAnts booth. Their conversation circled around a recurring theme at this year’s event: the uncertainty many organisations still feel about how to integrate AI into their systems in a structured way.
It was a candid exchange that reflected what many fintech leaders are grappling with. They spoke about risk, change management, and how enterprises are thinking about legacy modernisation. The discussion was clear, practical, and rooted in the realities of what companies are facing on the ground.
The AI Integration Crossroads
Across industries, enterprises are still approaching AI with caution. The hesitation is rarely about the technology itself. It usually begins with questions about strategic alignment, measurable outcomes, and operational impact. “The reason is mostly the risk factor,” Kunal Kumar said. “It involves various strategic decisions that come from the board about how they want to use it.”
This hesitation is linked to the internal weight of change. Adoption requires more than tools. It involves reshaping structures, creating new protocols, and ensuring teams know how to respond to shifting workflows. “It needs a lot of change management inside the organisation,” Kunal said. “Only then can you see it reflected in profit and loss.”
Another layer of complexity comes from the absence of clear frameworks. Many enterprises are uncertain about how to embed AI into their daily operations in a way that improves efficiency without disrupting core systems. “The framework is still not clearly defined on how AI will integrate into daily operational activities to actually improve efficiency,” he observed.
Modernising Legacy Systems
This hesitation is most visible in conversations about legacy system modernisation. At the GeekyAnts booth, many visitors described large, deeply embedded systems that support millions of lines of code. Their primary concern is not about the need to modernise. It is about doing so without bringing existing operations to a standstill.
Kunal explained that modernisation is not a new process. “Legacy system modernisation isn’t new. Even in the past, legacy systems kept getting modernised,” he said. “The only new element now is how you’re using AI in that process.” For him, clarity in framework and architecture makes the difference between risk and resilience. “If the framework is clear, the architecture is well-defined, and there is a proper protocol for using AI in coding, along with the right training for people, the risk becomes very low.”
What’s Next for AI and Fintech
As AI moves deeper into financial technology, the conversation is beginning to shift from tools to systems. Connected architectures and structured data frameworks are becoming essential. Within an organisation, information has to be easily accessible and reusable. Across borders, policies and protocols need to align.
Kunal is already looking ahead to what the next phase might bring. “I’d like to see more clarity around how fintech and AI are coming together,” he said. “We need clearer frameworks and risk controls. If AI integrates properly with existing fintech systems, it can transform client experiences.”
He also noted the excitement around upcoming shifts in payments. “Maybe next year, we’ll see AI-driven UPI demos. Payments will be handled by an AI agent without human input.” It is a vision that reflects the pace at which AI is beginning to shape financial transactions and trust infrastructure.
The Human Element
Amid these strategic conversations, the personal rhythm of the event continued. Kunal checked his step counter and smiled. Twelve thousand steps a day across the halls and corridors of the conference. Rakesh laughed as he shared his count from the previous day. The talk had shifted from frameworks to footsteps.
In the middle of an AI-focused global event, the value of human connection was clear. The handshake, the shared laugh, and the quick chat in a corridor all added to the atmosphere. It reminded them that while technology evolves, the foundation of every meaningful conversation remains human.
Do We Have The Social Permission To Use AI? If Yes, Then At What Scale?
Vidish Sirdesai
Let's be honest, we've all been captivated by the magic of AI. It feels ethereal, doesn't it? An intelligence living in "the cloud," crafting poetry, generating stunning images, and solving complex problems with what seems like zero physical effort. This perception of AI as a clean, weightless, digital entity is perhaps its greatest illusion. We’ve become so fixated on the incredible question of what AI can do that we’ve forgotten to ask a much more fundamental one: Do we have the social permission to use it? And if so, at what scale?
This isn't a call to reject technology or halt new developments. It’s about acknowledging a hard truth. Every single AI query, every model trained, and every breathtaking image generated has a physical, tangible, and alarmingly large footprint on our planet. The "social license" to operate—a concept industries like mining have grappled with for decades—is something the AI world has largely ignored. But as the true environmental costs come to light, it’s a conversation we can no longer afford to postpone. The permission to innovate must be weighed against the planetary price tag.
Beyond Carbon: The Voracious Appetite of the Digital Brain
When we talk about tech’s environmental impact, our minds immediately go to its carbon footprint. And for good reason. The enormous data centers that make AI possible are extremely power-hungry. Training a single large language model, like GPT-3, was estimated to consume enough electricity to power over 120 U.S. homes for a year, with a carbon footprint equivalent to flying from Bangalore to Dubai and back nearly 270 times. Every query we make is a part of this endless energy draw, a silent demand on a power grid still heavily reliant on fossil fuels.
But carbon is just the opening act. The hidden protagonist in this story is water. Think of a data centre as a super-athlete running a marathon 24/7. To prevent it from overheating, it needs to be constantly cooled, and the primary method is water evaporation. How much water? A 2023 study from the University of California, Riverside, estimated that training GPT-3 alone may have consumed 700,000 liters of fresh water. On a smaller scale, it’s estimated that a simple chat conversation of 20-50 questions with an advanced AI could be like pouring a half-litre bottle of water onto the ground. Now, multiply that by billions of users. This isn't just "virtual" water; it's real, physical water being drawn from local sources, often in drought-prone regions where tech giants build their facilities, pitting digital progress against the essential needs of communities and agriculture.
This demand ripples outward into a broader ecological footprint. Data centres require vast tracts of land, disrupting local ecosystems. The energy they consume contributes to air pollution, which in turn leads to the release of nitrogen oxides, creating a nitrogen footprint that can harm soil and water quality. It’s a cascading chain of consequences, all hidden behind our sleek, clean screens.
The Tangible Ghost: From Silicon to Landfill
If the operational costs are concerning, the physical body of AI is just as troubling. AI isn't just code; it's hardware. It's millions of specialised GPUs, servers, and networking cables, each with a finite lifespan and a toxic legacy. This is where the chemical, plastic, and e-waste footprints come into terrifying focus.
Think about what goes into a single GPU, the workhorse of the AI revolution. Its creation involves a concoction of hazardous materials—heavy metals like lead and mercury, flame retardants, and a slurry of caustic chemicals used to etch silicon wafers. The manufacturing process for these semiconductors has a significant chemical footprint, posing risks to factory workers and the surrounding environment, often in countries with laxer environmental regulations.
Then there's the plastic. Server racks, casings, miles of cables, and cooling components are all made from plastics derived from fossil fuels, contributing to a plastic footprint that we are only just beginning to measure. But the real kicker is the speed of obsolescence. The race for AI supremacy has triggered an arms race for ever-more-powerful hardware. Today’s cutting-edge chip is tomorrow’s e-waste. Where do these mountains of discarded servers and GPUs go? Too often, they are shipped to developing nations, ending up in landfills where their toxic chemical components leach into the soil and groundwater. AI’s progress creates a digital ghost in the machine, but its physical corpse ends up in a very real, very toxic graveyard.
Earning Our AI Future: The True Scale of Permission
So, back to our original question: Do we have the social permission to deploy AI at this scale? The answer, looking at this evidence, can't be an unconditional "yes." Social permission isn't a right; it's something that must be earned through transparency, accountability, and genuine responsibility.
Right now, the AI industry largely operates in an opaque box, with most major companies not disclosing the specific energy and water consumption of their models. Earning social permission starts here: with radical transparency. We, the public, need to know the true environmental cost of the services we use.
Permission is also earned through innovation—not just in making AI smarter, but in making it leaner. Researchers are already exploring more efficient model architectures, greener hardware, and less water-intensive cooling methods. This must become a priority, shifting the industry’s focus from a "bigger is better" mindset to a "smarter and more sustainable is essential" one.
Ultimately, the scale of our permission is tied to the scale of our responsibility. An unchecked, exponential expansion of the current AI paradigm is simply unsustainable. We need to forge a new social contract for AI, one where the undeniable benefits are rigorously weighed against the true planetary cost. It's not about stopping the train of innovation. It's about learning to steer it with wisdom. The ultimate test of our intelligence won't be in our ability to create artificial minds, but in our ability to deploy them without sacrificing our shared home.
A Moment in the Spotlight: GeekyAnts Featured at Global FinTech Fest 2025
The Global FinTech Fest 2025 brought together industry leaders, innovators, and policymakers from around the world to discuss the future of digital finance. At the centre of this gathering was a growing interest in how AI can strengthen financial infrastructure, improve customer experience, and shape modern payment systems. Against this backdrop, GeekyAnts emerged as a notable voice at the event, engaging directly with enterprises and industry leaders.
In the days following the event, the global and mail published a news article highlighting GeekyAnts’ role and presence. The coverage positioned the company’s contributions within a larger conversation around AI-first financial innovation, UPI’s global expansion, and the evolution of enterprise technology. It reflected the visibility that comes when technology strategy aligns with the pulse of a global industry moment.
The Coverage and the Stage
The global and mail carried the story under the headline “Fintech’s Next Frontier: GeekyAnts at Global FinTech Fest 2025 Showcases AI-First Financial Innovation.” Published on October 10, 2025, the article focused on how the company participated in the event in Mumbai as a delegate and exhibitor. It detailed the themes that dominated the floor, from PayPal’s global UPI announcement to the growing urgency around modernising legacy infrastructure.
The article emphasised the intersection of AI adoption and enterprise readiness. It outlined how organisations are seeking structured approaches to integrate AI into their systems, highlighting statements from GeekyAnts leaders on the importance of discipline and customer centricity. These themes echoed across the event, where AI was central to many conversations, products, and strategies.
The Global FinTech Fest has rapidly grown into one of the most influential gatherings in the sector. Its evolution from a regional event into a global stage for digital payments has mirrored the pace of innovation happening across India’s financial technology landscape. Coverage of GeekyAnts within this context reflects how the company’s work is finding its place within a larger narrative of transformation.
Inside the Conversation
The article featured insights from Kunal Kumar, COO of GeekyAnts, who spoke about the importance of structured frameworks when working with AI. His observations on balancing capability with risk underscored a pragmatic understanding of how technology must be implemented within financial ecosystems.
Shreya Mago, Senior Consultant at GeekyAnts, was also quoted, reflecting on the need to keep customer priorities at the centre of technological advancement. Their perspectives in the article offered a clear picture of the company’s position within the conversation: focused on practical adoption, clarity of purpose, and measurable impact.
Recognition and Reach
External coverage of an industry event carries weight when it highlights substance over spectacle. The reporting on GeekyAnts places emphasis on strategic themes that resonate across the sector: AI-first innovation, modernisation of enterprise systems, and the global expansion of UPI as a trusted payment infrastructure.
For GeekyAnts, this moment illustrates how the company’s voice is becoming visible in spaces where the future of financial technology is being shaped. The press coverage functions as a mirror to the conversations taking place across the industry. It reflects how the company’s participation is tied to the larger momentum of digital finance.
The recognition also signals a shift in how AI and connected data are being understood in the financial sector. Beyond products and platforms, the focus is moving toward building resilient systems, and the company’s expertise is part of that progression.
Charting the Road Ahead
Being featured in external coverage of a global industry event adds a layer of public visibility that extends beyond the walls of the conference hall. It marks a moment of presence within a fast-evolving ecosystem and places the company within a larger network of conversations shaping the future of finance.
As AI continues to reshape financial services, visibility of this kind creates new possibilities for collaboration, learning, and shared progress. It captures a point in time where strategy, technology, and industry attention intersect — and sets the stage for what comes next.
Global Fintech Fest 2025 — A World in Transition
The Global Fintech Fest 2025 in Mumbai brought together leaders, innovators and policymakers from across the financial technology landscape. The conversations made it clear how deeply technology has become part of the financial system. It was a meeting point for industry strategy, regulatory priorities and technological ambition.
Across the sessions, a single idea kept resurfacing. Technology has moved to the centre of how financial services are designed and delivered. Every major theme, from banking models to payments infrastructure and digital identity, reflected this shared understanding.
A Global Shift in Banking and Finance
The financial sector is entering a phase defined by technology-led transformation. Institutions that once depended on legacy systems are reorganising their core structures around software, data and digital platforms. This shift was visible in every conversation that explored how banks and financial service providers are reimagining their future.
One statement captured the spirit of this moment. “Banks of today will be the technological companies of tomorrow with the licenses.” It was presented not as a prediction but as an observation. Financial institutions across the world are investing in technology as the foundation of their identity and not as a supporting function.
The language of finance is also evolving. Terms that once belonged to technology have become part of everyday conversations inside boardrooms and regulatory circles. This blending of vocabulary signals a deeper blending of structures. The global financial system is being rebuilt in real time with technology at its core.
India’s Fintech Momentum
India’s fintech ecosystem occupied a central place at the festival. The country’s digital public infrastructure has enabled financial services to scale with remarkable speed. Systems such as UPI and Aadhaar have become integral to how millions of people engage with banking and payments. This foundation has created room for innovation that is both broad and deep.
Many of the conversations focused on how AI is being used to support this growth. Startups and established players are deploying it for credit assessments, secure transactions and personalised customer experiences. These are no longer early-stage experiments. They are live systems with measurable impact.
The tone of these discussions reflected maturity. Participants spoke less about promises and more about systems that are already in motion. The focus was on improving reliability, security and access rather than announcing abstract ambitions.
Collaboration was a defining feature of India’s presence at the festival. Policymakers, banks and startups described their work as part of a shared ecosystem. This sense of collective ownership has made India’s fintech story both ambitious and grounded.
AI at the Heart of Transformation
Artificial Intelligence was a constant thread through the event. It appeared in conversations on infrastructure, security, identity and customer experience. Its role is no longer speculative. It is embedded within the way financial systems are designed and maintained.
Its uses are growing steadily. AI is supporting real-time compliance checks, improving onboarding journeys and strengthening fraud detection. It is also enabling more responsive and context-aware customer interactions. These are practical deployments that are shaping daily operations in banking and fintech.
The presence of AI did not need to be announced. It was already part of every discussion, folded naturally into the architecture of modern finance.
A System That Is Taking Shape
The most defining aspect of GFF 2025 was the sense of alignment across the ecosystem. Banks, fintechs, regulators and technology partners are working more closely than ever before. This shared effort is shaping the structure of tomorrow’s financial systems with clarity and purpose.
India’s position in this evolving landscape is both local and global. Its infrastructure is rooted in national priorities while contributing to a wider network of innovation. The future of fintech will be defined by how these shared systems continue to grow, mature and find common ground between trust, intelligence and scale.
Humans of GeekyAnts: Stories and New Joinees
When I joined GeekyAnts five years ago, I was eager to see how engineering intersects with real-world business challenges. Working with some of the biggest names in the industry has been an incredible journey of growth, problem-solving, and continuous learning.
Every project has been different — new domains, new technologies, new expectations — and that's what has made this experience so rewarding. Collaborating closely with clients, both domestic and international, has taught me how to translate technical ideas into meaningful solutions that drive real impact. It's pushed me to think not just like an engineer, but like a partner invested in our clients' success.
One highlight that stands out is leading the creation of a cutting-edge, innovative and in-house scalable solution for one of the largest companies in India. Moments like these remind me how powerful teamwork, innovation, and trust can be when we align around a shared goal.
Looking back, GeekyAnts has given me far more than just professional experience — it's given me a platform to learn from brilliant minds, innovate, take on exciting challenges, and grow into a more confident, adaptable engineer. I'm proud to be part of a team that builds not only great technology, but lasting relationships. Ankit Pandit
Five years in, and it still feels a bit surreal. I joined as a nervous fresher who could barely stitch a product end-to-end; mentors here helped me learn the craft. I’ve had the rare chance to build across healthcare, banking, real estate, and e-commerce—and nothing beats the quiet thrill of seeing people use something you shipped.
People say devs don’t have work–life balance. For me, it’s passion: when I spot a problem, I want to solve it. That curiosity has shaped my growth and, honestly, raised the bar for what I expect from my own work. When doors were closed, I learned to make a way—and to back myself even when it sounded a little bold.
This place has been a classroom, a launchpad, and a team I’m proud to learn from. My mantra along the way: don’t touch it before a release—nobody likes surprises on release day. - Roshan Kumar Ojha
It’s hard to believe it’s already been seven years at GeekyAnts! When I first joined, I was just excited (and a bit nervous) to be part of a company that lived and breathed technology. Over the years, GeekyAnts has become so much more than a workplace — it’s been a space for learning, experimenting, growing, and most importantly, belonging.
From my early days of exploring new tech stacks to working on products that truly make a difference, every step has shaped me both professionally and personally. I’ve had the chance to collaborate with incredibly talented people who’ve inspired me to keep pushing my limits and stay curious.
One of the moments that will always stay with me is “the first project I led as QA ,the project launch day, the day our team pulled together to meet an impossible deadline”. It reminded me what makes GeekyAnts special — the culture of teamwork, innovation, and trust that runs through everything we do.
Looking back, this journey has been a blend of learning, laughter, challenges, and countless memories. I’m grateful to have grown alongside GeekyAnts — and I’m excited to see where the next chapter takes us - Surabhi Suman
New Joiness
@Tejas Pratap – Software Engineer In Platforms I
A Computer Science graduate with hands-on experience in DevOps and backend development, Tejas has worked with Docker, Kubernetes, Jenkins, and Prometheus to build scalable systems. He’s also a professional Valorant player, a guitarist, and loves exploring new tech tools!
@Anand Kumar – Software Engineer II
An experienced Java Developer skilled in Spring Boot, Microservices, AWS, Docker, and Kubernetes. Anand excels at building CI/CD pipelines and follows Agile methodologies. Off work, he enjoys cricket, TT, and football!
@Kiran N – UI & UX Designer
Kiran brings around 2 years of experience in crafting intuitive and impactful digital experiences. Previously at OneIndia (Greynium), Kiran led UX/UI projects for large-scale content and data-driven platforms. With expertise in user research, interaction design, and product thinking, Kiran loves transforming complex problems into clean, thoughtful design solutions. Outside of work, Kiran enjoys bike rides, movies, and following cricket — especially those nail-biting India matches!
@Sriram Devaraj – Senior Software Engineer I
Sriram brings 5.5 years of experience as a Java Backend Developer, skilled in Spring Boot and Microservices. Previously, he worked with Tata Consultancy Services as a Software Engineer. Beyond coding, he enjoys playing cricket and football, and loves listening to music in his free time!
@Aarti Navlakhe – Senior Software Engineer I
Aarti is a Backend Developer with 3.3 years of experience in Java, Spring Boot, and Microservices development. She specialises in designing and implementing scalable microservice architectures that enhance performance and efficiency. Outside work, Aarti enjoys sketching and playing badminton!
Systems and Design at GFF Mumbai 2025
The Global Fintech Fest 2025 in Mumbai was more than an exhibition of financial technology. It was a reflection of an industry trying to define its purpose. Banks, startups, investors, and policymakers gathered to exchange ideas about the future of money, yet the substance of the discussions pointed toward something deeper than innovation. It was a conversation about infrastructure, governance, and trust.
Walking through the venue, the scale was undeniable. Booths, panels, and stages formed a continuous dialogue between ambition and accountability. Beneath the language of disruption was an unspoken recognition that fintech has reached a stage where reliability matters more than novelty. The discussions felt less about invention and more about refinement.
The festival’s size mirrored the scope of modern finance itself. Every domain, from payments to lending to analytics, appeared interconnected. What emerged was a portrait of fintech as an ecosystem under construction, aware of its power but still searching for stability.
Architecture and Accountability
The most revealing insight from this year’s event was the collective shift toward systems thinking. For years, fintech gatherings celebrated growth metrics and funding rounds. This time, conversations turned toward architecture. Architects and engineers spoke about replatforming, interoperability, and data lineage. The language of scalability became a language of responsibility.
Discussions around cloud-native transformation were no longer confined to technology vendors. Large banks, long reliant on legacy cores, spoke openly about their plans to modernise. Many outlined clear timelines for adopting microservices and real-time data streaming. The vocabulary of enterprise technology has entered the boardroom, and with it comes a recognition that technical debt is now a business risk.
The absence of deep technical debate on security and compliance was noticeable. Few sessions addressed encryption frameworks or regulatory enforcement. Yet the undertone across many conversations was unmistakable. The industry knows that credibility will depend on adherence to standards that extend beyond convenience and speed. The next wave of fintech engineering will need to embed auditability and explainability into its core design.
Scalability, once an abstract ideal, is now an operational demand. Fintech products process millions of transactions daily, and with that scale comes exposure. Architects and solution designers are beginning to think of performance not as a feature but as an assurance. The measure of success lies in systems that can sustain growth without compromising the integrity of data or user trust.
The Design Convergence
While engineering dominated much of the discourse, design made its presence felt as a central pillar of financial credibility. At the GeekyAnts booth and across many others, conversations focused on design systems that translate complexity into clarity. Founders and design leaders spoke about accessibility, inclusion, and transparency as the foundation of user confidence.
UI and UX are no longer being treated as layers of polish. They are becoming the first expression of compliance. In a sector where trust determines adoption, every element of visual and interactive design communicates reliability. The interface is where architectural integrity meets human experience.
The most forward-looking teams described AI-assisted design systems that help personalise financial journeys while maintaining consistency with regulatory design standards. Designers are now working alongside engineers to automate aspects of accessibility and localisation. The result is a subtle merging of design and governance — a process where aesthetics and accountability evolve together
The Missing Bridge
What still separates fintech’s ambition from its potential is the gap between technical structure and user experience. Architecture and design often operate in parallel rather than in dialogue. The systems that move money and the interfaces that explain those movements rarely share the same language.
The next phase of maturity for fintech will depend on uniting these disciplines. Reliability must become visible through interface behaviour, and transparency must be supported by backend logic. When architecture and design evolve together, users experience stability not as an abstract idea but as a daily reality.
Institutional Change
Legacy institutions, once cautious observers, have begun to act with intent. Banks burdened by decades of technical debt are outlining detailed modernisation roadmaps and identifying technology partners who can participate in long-term rebuilding. These conversations have moved from pilot projects to system-wide plans. Core platforms are being re-evaluated, and the focus has shifted toward modular architectures that can grow without adding complexity.
The appetite for transformation is now structural. Large institutions are investing in cloud infrastructure, integration layers, and data strategies that connect legacy records with real-time analytics. The work is slow but deliberate. Each layer that becomes interoperable adds a degree of resilience to the whole network of digital finance.
Continuity and Trust
GFF 2025 captured an industry learning to value durability. Behind every announcement lay a shared understanding that technology and design will determine how users experience reliability. Architects are refining the foundations of data movement and compliance. Designers are translating that reliability into clear and credible interfaces. Both efforts point to the same goal: systems that invite confidence through consistency.
The progress that matters most will unfold in the background. It will appear in cleaner codebases, accessible interfaces, and documentation that explains without ambiguity. The future of fintech depends on this quiet work — the effort to make complex systems stable, transparent, and worthy of trust.
Strategic Partnerships: The Engine of Growth and Innovation
This month revealed how strategic partnerships create measurable value across our operations. Our collaboration with a key technology partner unlocked faster access to key resources across projects like a leading financial services platform, an enterprise workflow solution, a process management client, and a product engineering initiative, directly accelerating delivery timelines. The seamless coordination and trust we've built have enhanced our credibility with clients, making it easier to push complex initiatives forward.
Strong partnerships actively create new possibilities beyond project support. The coordination between teams generated efficiencies that neither side could have achieved independently, proving that value emerges when knowledge flows freely between partners.
Market Positioning and Collaborative Solutions
A strategic partner in embedded systems continues setting the standard in hardware, firmware, and Linux development alongside on-demand talent and customised solutions. GeekyAnts positions itself as a proactive enabler in this landscape, helping clients scale efficiently by staying ahead of market trends. Our ability to adapt quickly and deliver innovative solutions differentiates us in a competitive market.
This month's projects highlighted how co-developing solutions reveals efficiencies invisible to individual organisations. The focus moving forward centres on structured feedback loops to maximise collaborative learning. These mechanisms will capture insights that emerge naturally from partnership work.
A notable milestone was our reengagement with a staffing solutions partner, which successfully fulfilled two TO positions in a major financial institution. Deploying these resources strengthens client relationships and demonstrates how collaborative staffing solutions drive meaningful impact.
Speed and Responsiveness as Core Strengths
Our work providing replacement profiles for a digital solutions partner showcased the speed and creativity that define our approach. The partner's appreciation for quick candidate deployment in the financial institution project confirmed that responsiveness creates lasting value. Our openness and agility stood out across multiple engagements this month.
These qualities transform partnerships beyond transactional relationships. The rapid turnaround times and quality of deployment reinforced our reputation as a reliable collaborator. Partners recognise that working with us means accessing solutions quickly without compromising on quality.
The combination of speed, technical capability, and collaborative mindset positions us distinctively in the market. This integrated approach addresses client needs while building partner confidence in our ability to deliver under pressure.
Sustained Growth Through Partnership
This month confirmed that deep collaboration unlocks better project outcomes and new working methods. The momentum we have built with partners like our key technology and staffing collaborators creates a foundation for sustained growth. Structured feedback mechanisms will help us capture learnings and apply them across future engagements.
Our commitment to speed, openness, and technical excellence continues to drive partnership success. These partnerships benefit all stakeholders by combining capabilities and creating solutions neither party could achieve alone.
October BA Report: Every Line Accounted For
BA team went line by line, matching each backlog item to its design reference and technical note. Documentation was rewritten as the work progressed, replacing partial comments with complete user stories. By the end of the cycle, what had been a collection of scattered notes had turned into a sequence of traceable requirements.
The same pattern repeated across projects. Analysts closed the gap between what teams were building and what clients expected by turning feedback into structured updates. In one case, a delay in a payout workflow was traced to missing validation rules; in another, a set of onboarding screens was refined to remove redundant flows. Each fix was small, but together they restored continuity in delivery.
Much of October read like that — granular work with visible effect. Every project carried a slightly different texture, yet all pointed in the same direction: analysis becoming the connective tissue of execution. The month was measured not by launches or announcements but by the number of issues that no longer needed explanation.
Making Delivery Predictable
Impact was recorded in the flow of work rather than its presentation. Teams documented every requirement revision, release note, and dependency trace in a central space, creating a live record that kept development and QA aligned. A project that had struggled with release timing began closing sprints with complete documentation and predictable approvals. The same cadence appeared elsewhere, and delivery meetings turned into working sessions that resolved ambiguity instead of generating new tasks.
In one of the larger projects, a new payout mechanism was finalised after weeks of incremental fixes. Each step was logged, reviewed, and confirmed before merging. The onboarding flow that followed was built on the same rhythm, with each screen mapped to a user scenario and validation rule. Elsewhere, the Canva-style editor reached production stability, integrating design freedom with constraint management. Content management at go-live became a structured process with clear ownership and version tracking.
These improvements did not arrive from a top-down direction. They came from smaller decisions: rewriting a single acceptance criterion, clarifying a dependency chain, scheduling a recurring review at the right stage. The team treated the process not as a template but as a living reference, adjusting details as each project revealed its specific friction points.
By mid-month, the results were visible across the dashboard. Handoffs were cleaner, scope deviation reports were shorter, and fewer blockers escalated to management. Impact could be read in the calm predictability of delivery, a rhythm that carried its own confidence.
Turning Practice into System
Analysts focused on tightening the structure that held projects together. QA trackers were rebuilt to connect test outcomes with requirement stories, creating direct visibility between what was written and what was verified. Documentation audits replaced scattered handover notes with indexed templates that carried version history and context. Jira issue types were refined to mark dependencies clearly, and sprint reviews began using visibility sheets that traced each feature from scope to completion. These actions made progress easier to follow and reduced time spent aligning across teams.
The effort gave the BA function a stronger internal memory. Information moved cleanly between cycles, and new contributors could read the logic of a project without starting from scratch. Consistency stopped depending on individual recall and started living inside the system itself.
Upstream Work, Earlier Influence
Several analysts began contributing at the proposal stage rather than after project sign-off. They joined discovery meetings, prepared user flows for early estimates, and reviewed feasibility with designers and engineers before documentation began. In pre-sales for projects such as a creative storytelling platform and an enterprise collaboration tool, requirement outlines and scope assumptions were checked against technical limits, which helped shape proposals that could move directly into build without revision. The same approach appeared in a mobility-focused application, where preliminary flows clarified dependencies before contracts were finalised.
Early participation changed the rhythm of work. Estimates became more reliable because risks were identified while they could still be adjusted. Teams entered design and development with stable baselines and fewer unknowns, and clients saw shorter turnaround between approval and execution. Analysis became integral to planning, influencing how projects began and evolved.
Tools as Policy
Tools carried equal weight in shaping the team’s behaviour. Miro retros replaced scattered feedback calls, capturing every observation where everyone could see it. GitHub check-ins became part of the BA workflow, ensuring traceability between documentation and code commits. Each small change reduced the invisible effort of backtracking decisions.
Jira issue types were customised to surface blockers automatically, removing the need for repeated follow-ups. Analysts began tracking delays in context, not as isolated tickets but as signals of coordination gaps. The shift from chat-based reminders to structured issue logging created a more visible record of accountability.
Lovable, adopted as a design interface tool, shortened design-to-BA feedback loops. It allowed teams to comment on active prototypes without leaving the platform, reducing translation errors. These choices made tools a form of policy — behaviour encoded in structure rather than instruction.
October Sales Report: What Built Credibility
Conversations this month began with preparation that shaped perception early. At an education technology client, the discussion around an AI avatar for student training shifted once the team outlined the recurring costs of AI integration. The client’s priorities moved from speed of delivery to sustainability, and the conversation opened into a practical review of long-term value. This single insight redefined intent, creating room for trust and measured decision-making.
A similar moment occurred with an engineering solutions firm. The team entered the first call with a complete user journey and a structured presentation. The client’s response was grounded in confidence rather than curiosity. Preparation became a form of proof. By showing the logic of execution before any negotiation began, the relationship moved forward with a clear sense of alignment.
Reading the Prospect
A compliance-focused enterprise revealed how regulation can shape value. In the early discussions, the client’s attention stayed fixed on requirements specific to its operating region. The team paused to research obligations around personal data and operational permissions, then rewrote parts of the proposal to meet those constraints. The adjustment turned an initial inquiry into a credible plan for deployment.
A mobility platform client offered a different lesson. The first architectural suggestion raised concerns about scalability. Instead of defending the design, the team gathered client references, studied comparative systems, and prepared a revised approach. This response reframed the engagement as cooperative planning, not transactional delivery.
Across these projects, the same insight became visible. Prospects respond to preparation that demonstrates comprehension of their domain. Value lies in knowing what matters to the client before they articulate it. Each correction in structure or framing strengthened the foundation of trust.
Measured Risk
A technology startup illustrated what deliberate initiative can achieve. The team proposed an initial audit before any formal agreement. The decision placed evaluation ahead of commitment and allowed both sides to understand the environment without pressure. The client accepted, and the engagement moved forward with clarity rather than assumption.
This step was less about risk and more about proportion. It allowed the team to show competence in the client’s context without commercial framing. When value became visible, interest followed naturally. The discussion stayed grounded in evidence rather than intent.
Each of these moves reinforced a larger pattern. Initiative is not defined by volume or persuasion but by readiness to begin from substance. The audit demonstrated the team’s capability to act responsibly in uncertain ground, setting a tone of reliability that carried into later discussions.
Collaboration as Leverage
At the mobility platform client, estimation, analysis, and engineering sat over the same requirements list and broke it down line by line. The estimation team recalculated effort based on design dependencies, analysts rewrote ambiguous user stories, and engineers tested the feasibility of integration points before the proposal left draft form. The single shared document that emerged carried estimates, flow diagrams, and validation notes together. The client called it the first time they could see “how it all fits,” and from that meeting onward, the dialogue moved from interest to intent.
That degree of internal alignment changed the pace of every later update. With requirements, design impact, and timelines already reconciled, follow-up questions disappeared. The document itself became a working agreement, and each team involved could trace its contribution without overlap or uncertainty. What began as preparation turned into an operational habit that shortened the path from discussion to delivery.
What Builds Trust
Trust grew out of precision. Clients reacted to the evidence of preparedness: cost projections that held under review, compliance notes that matched regulation, and architectural plans that survived scrutiny. These details carried weight because they were verifiable. The record of October shows that prospects responded most when information was already tested against their reality.
Across projects, this clarity produced the same outcome. Proposals were approved faster, technical discussions stayed open longer, and collaboration deepened once proof replaced intention. The work of the month made one idea unmistakable: reliability is not a trait but a structure built through accuracy, traceability, and patience.
Value Of The Month
Collaboration
Ideas rarely arrive fully formed. They emerge fragment by fragment, passed between minds like stones shaping a riverbed. One person sketches possibility, another questions its edges, a third finds the thread that binds disparate thoughts into something whole.
This slow alchemy demands patience—the willingness to surrender ownership, to let your half-finished thought become someone else's starting point. It requires trust that the collective vision will exceed individual brilliance.
At GeekyAnts, we've learned that the best work happens not when everyone agrees, but when everyone listens, challenges, and builds together.
Notes from the Studio: Design Team Highlights
Across the design studio, this month’s work turned toward the essentials. The projects varied in domain and complexity, yet all shared a single motive: to make interaction feel lighter without losing its depth. Each designer faced a surface crowded with possibilities — from dense grids to evolving systems — and worked toward a state where information arranged itself with quiet confidence.
What emerged was less about invention and more about precision. A few patterns, a few labels, a single motion — each refined until the idea felt self-evident. The stories that follow trace this process of reduction, where clarity became not an aesthetic choice but a working method.
The Pursuit of Clarity
In a component library project, Chandravardhan began by questioning how users read truth and falsehood on a screen. The existing radio buttons shifted labels when toggled, creating momentary doubt. Through testing, the team saw that predictability mattered more than variety. They removed radio options and standardised checkboxes and toggles. The client’s response — “Finally, I can see only what matters” — confirmed that clarity can register in a single instant.
The next refinement went deeper than interface polish. By aligning the dynamic label behaviour with a logical rhythm, the design reduced friction across states. What looked like a small decision about text and controls became a structural change. The interface no longer demanded interpretation; it communicated its purpose by being consistent.
This clarity extended into collaboration. When engineering questioned how dynamic labels would translate to implementation, a prototype replaced speculation. The moment the working model appeared, alignment followed. Design became the proof rather than the argument.
A Language of Systems
While one team refined semantics, another explored adaptability. Megha approached her work on a wellness and lifestyle application as an exercise in resilience — how a design system maintains coherence while stretching across audiences. She tested multiple colour groups, allowing the interface to stay legible against extremes of contrast. Font scaling for accessibility was calibrated to expand without deforming the layout. The outcome felt deliberate: inclusive without breaking its own form.
Her loader design carried this philosophy forward. It held brand identity not through ornament but through motion. When seen together, these decisions revealed a belief that systems express empathy through consistency. A design system is not a grid of components; it is a living vocabulary that learns how to stay whole under pressure.
When Intelligence Enters Design
Clarity began in an unexpected place — within a recipe. Working on a smart nutrition platform, he discovered that artificial intelligence could generate meal ideas that responded to user habits. The finding was not technical novelty but a shift in creative authorship. By integrating AI-generated content into the interface, he created a loop where the product could suggest, learn, and adapt.
The onboarding and pantry flows carried the same sensibility. Card-based layouts replaced complex menus, guiding new users with direct visual cues. The effect was immediate usability. A prototype captured these movements precisely, allowing both design and engineering to see the sequence before it was built. In the finished product, every transition had reason and proportion. Intelligence did not add complexity; it redistributed effort between designer, system, and user.
Seeing the Whole Picture
Nuthan’s work on a tracking interface took clarity into a spatial dimension. His client wanted every alert, map, and vehicle detail to sit within one environment. The first version achieved that unity, and the client’s message — “Everything we need is in one place” — confirmed the goal. Still, refinement continued. The layout evolved until the map, controls, and notifications formed a single field of attention.
The interface supported three languages, each tested to preserve rhythm and balance. A vehicle trail playback feature added temporal understanding to the visual one. Users could watch movement unfold along a chosen path and time, a feature that made data feel tangible.
To preserve visibility, the bottom navigation bar transformed into an expandable element. It retracted when focus shifted to the map and returned when navigation was required. Through these layers, clarity became motion rather than stillness.
After the design phase, the process extended into joint testing with developers. Each interaction was checked against the original intent until the implemented version mirrored the plan. Collaboration worked as the final lens, keeping the design’s precision intact through delivery.
The Culture of Refinement
Across these projects, a single practice held steady — using prototypes as a common language. Each designer, in different circumstances, turned to working models to resolve uncertainty. Visualising interaction allowed teams to agree faster than conversation alone could achieve. Clarity was built in public view, frame by frame.
This method reflects more than workflow; it defines a culture. When clarity becomes a shared responsibility, design matures beyond aesthetics. The craft lies in knowing when a system communicates enough, when a label carries its meaning, when an animation explains itself. The month’s work closed on that understanding: every decision, however small, contributes to an experience that users read without effort.
Overthink Tank
Facts Section
- WebP typically delivers images 25–34% smaller than JPEG at equivalent visual quality, which can be a big win for Largest Contentful Paint (LCP) budgets.
- iOS and iPadOS 16.4 added standards-based Web Push, so home-screen web apps (PWAs) on Apple devices can send push notifications using the same Web Push API used on desktop.
- Figma was set to be acquired by Adobe Inc. for approximately USD 20 billion in cash and stock when the deal was announced on 15 September 2022.
- In a study by GitHub, developers using Copilot had a 53.2% higher chance of passing all ten unit tests in the controlled task.
- Google’s food-service division uses behavioural design strategies—such as smaller bowls and data-driven adjustments of menu items—to reduce cafeteria food waste by up to 70% in pilot locations.
Joke Section
- Why did the frontend developer break up with the backend developer? Because they kept saying, “It’s not my API type.
- Why don’t AI models ever panic? Because they already lost all sense of human context in training.
- A junior asked what legacy code means. The senior sighed and said, “Job security.
- Every company has transparency—right up to the NDA.
- Our AI assistant flagged a bug in the documentation. The word was ‘approximately.
Comic
Description of the image: A designer presents two identical screens. The client squints. Client: “I like the second one more.” Caption: There was no second one.
Diwali at GeekyAnts: A Celebration of Light, Colour, and Good Food
The Diwali celebration at GeekyAnts brought everyone together in the cafeteria, where the afternoon slowly turned into an evening of activity, conversation, and shared fun. The day had already begun on a bright note, with people arriving in traditional clothes—saris, kurtas, sherwanis, and lehengas in every colour. Many shared what made their outfit special: a sari stitched by a parent, a skirt made at home, a kurta chosen for its cultural connection, or a look put together just the night before. These small stories gave the gathering its own sense of character.
Lunch was a highlight, with puris, aloo, paneer, and sweets filling the tables. Soon after, the cafeteria was rearranged for the evening’s events. Multiple activities began at once—diya painting, lantern making, and rangoli design—each corner of the room filled with colour, paper, paint, and conversation. People moved freely between tables, helping each other finish designs or stepping aside to see how others were doing. There was music playing in the background, a mix of laughter and casual competition that made the space feel easy and full.
At the same time, the Fortune Cookie game kept everyone guessing. It had two versions—light mode and dark mode—and participants could pick a cookie only after completing one of the creative activities. Hidden inside five cookies were Amazon vouchers, and each reveal brought applause, jokes, and a brief pause before the next round began. The mix of art, food, and play gave the evening a steady rhythm.
As the activities wound down, the cafeteria remained busy with people comparing designs, clicking photos, and staying back to talk. The lights reflected off the painted diyas and paper lanterns, and traces of colour and glitter stayed on the tables long after the games were over. It was a simple, collective celebration—rooted in food, creativity, and the pleasure of being together in one space.
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