In an period outlined by knowledge complexity, regulatory scrutiny, and AI’s insatiable starvation for context, Mohan Kumar has emerged as one of many few engineering leaders able to fixing for the longer term, whereas constructing at hyperscale within the current.
Because the Head of Engineering at AtoB, Kumar has helped architect a few of the fastest-growing infrastructure within the fintech house, propelling the corporate from early traction to a projected $100M+ income run charge in beneath three years. However his affect runs far deeper, into the very material of how knowledge is recorded, audited, and trusted throughout methods.
From Wall Avenue to Silicon Valley: A Bi-Temporal Origin Story
Kumar’s journey into knowledge temporality started not in academia, however on Wall Avenue. At hedge fund D. E. Shaw in 2010, he was tasked with constructing a system able to ingesting tens of millions of market ticks per second, a problem that led him to pioneer bi-temporal database structure.
Not like conventional databases, bi-temporal methods observe two timelines: the occasion time (when one thing truly occurred) and the statement time (when it was recorded). In high-frequency buying and selling, that distinction is important; a delay of even milliseconds can imply the distinction between revenue and peril.
Since then, Kumar has introduced this innovation to sectors as various as payroll (Zenefits), AI ethics (LinkedIn), and now real-time funds and compliance (AtoB).
Making Complexity Accessible
For years, bi-temporal knowledge fashions had been the area of large enterprises with specialised groups. Kumar modified that. Drawing on cloud primitives and full-stack frameworks like Rails and Django, he developed a technique that lets startups construct production-ready bi-temporal methods utilizing off-the-shelf instruments, in weeks, not months.
This method unfold virally amongst founders and buyers he mentored, with a few of these startups now reaching unicorn standing.
“A number of founders constructed audit-ready, compliant methods proper after their seed spherical utilizing my playbook,” says Kumar. “It was my method of giving again, turning proprietary engineering right into a group multiplier.”
Constructing the Future Rails of the Bodily Economic system
At AtoB, Kumar’s philosophy round auditable fintech primitives grew to become the inspiration for explosive progress. He led the event of a double-entry, bi-temporal ledger system that integrates seamlessly with a number of banking companions, powering merchandise like real-time pay-ahead factoring, a 24/7 liquidity service that’s redefining logistics financing.
By coupling foundational engineering with buyer empathy, Kumar enabled AtoB to scale 5x year-over-year, serving a historically underserved market with magnificence and precision.
Why Temporal Infrastructure Issues in an AI World
Kumar believes that bi-temporal knowledge isn’t only a backend selection, it’s an moral crucial. In domains like ESG reporting, healthcare, and AI governance, temporal constancy is the one method to make sure transparency.
“Think about a flu prognosis,” he explains. “If the onset date was three days in the past, the remedy protocol modifications. That very same logic applies in AI, understanding what knowledge was used, when, and in what context is crucial for compliance and belief.”
He’s seen this play out firsthand at LinkedIn, the place cataloging mannequin inputs and outputs throughout time allowed for privacy-first AI improvement, a playbook now turning into trade normal.
Recommendation for Founders within the AI-vs-Infra Dilemma
Requested what early-stage founders ought to prioritize in right now’s bifurcated startup ecosystem, Kumar’s recommendation is pragmatic:
“There’s no such factor as a CRUD-only or AI-only firm. Each profitable firm ultimately turns into each. Spend money on your knowledge foundations early, round Collection A, as a result of they’ll decide how briskly and the way far you may scale.”
He additionally cautions towards the romanticism of quitting too quickly:
“Your 9-to-5 funds your life; your 5-to-9 funds your dream. Validate your area of interest, affirm your product-market match, and solely then construct full-time.”
Giving Again, Not Locking Down
Regardless of being on the bleeding fringe of infrastructure design, Kumar has deliberately prevented patents. As an alternative, he opts to share information by way of open mentorship, whiteboarding classes with VCs, and hands-on steerage with founders.
This ecosystem mindset is shaping the subsequent era of startups. A number of VC corporations now advocate his playbook as a part of their early-stage assist, a testomony to the sensible, repeatable affect of his concepts.
What’s Subsequent: Temporal Engines for Autonomy
Trying forward, Kumar envisions a world the place autonomous mobility and usage-based monetary merchandise require even deeper temporal intelligence.
“Autonomous automobiles have to log when a sensor failed vs. when the system detected it. Fintech wants real-time traceability for compliance. Bi-temporal methods present that spine.”
Because the world hurtles towards a extra autonomous, AI-integrated future, Mohan Kumar’s imaginative and prescient, one which spans time itself, could very nicely develop into the invisible infrastructure powering all of it.
Designing for the Subsequent Decade, Not Simply the Subsequent Deployment
In an age the place AI brokers function autonomously, the place compliance isn’t a checkbox however a real-time necessity, and the place customers demand transparency from the methods that govern their lives, time itself turns into infrastructure. And Mohan Kumar is without doubt one of the few engineering leaders constructing at that depth.
What began on Wall Avenue as a necessity for velocity has matured right into a philosophy of belief, traceability, and open scalability. Kumar’s dedication to creating this philosophy accessible, from mentoring founders to embedding open-source rules into mission-critical methods, marks a shift in how deep tech reaches the market.
The long run will demand infrastructure that treats time as a first-class citizen, methods able to reasoning throughout historic and future states, adapting to real-time context, and assembly the best requirements of auditability, compliance, and moral AI. At AtoB, Mohan Kumar is not only making ready for that future, he’s actively engineering it. Drawing on his foundational work in high-frequency buying and selling at D. E. Shaw, constructing payroll infrastructure at Zenefits, and advancing AI transparency at LinkedIn, Kumar is now shaping the rails of the bodily and monetary financial system. His work at AtoB is setting new benchmarks for the way fashionable fintech platforms scale, with velocity, belief, and a deep respect for the integrity of knowledge throughout time.
