Fractional CTO · Technology & Product Leadership
Shrinath Balakrishnan
I turn business problems into working technology — and keep it lean enough that the tech budget never becomes the story.
Eight years as co-founder and CTO of Source.One, owning technology and product for one of India's largest B2B industrial distribution businesses.
Source.One, FY2018–FY2026.
What I do
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Be the tech brain of the business
Understand the problem from the business's side first, then translate what leadership needs into what actually gets built.
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Right-size the team and the roadmap
Build for the business you have, not the one in the deck. I'll tell you whether you're buying speed or cost — you rarely get both.
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Ship AI/ML where it moves a number
Pricing, cost prediction, document and conversation automation — with a P&L outcome attached, not a pilot that never leaves the deck.
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Fix what you've inherited
Architecture reviews, salvage-or-rebuild calls, migrations off the system you've outgrown. I've made that call under a live deadline.
Selected work
Three decisions that shaped a ₹3,000 Cr business
Judgment under constraint
The platform I threw away in week one
Inherited an unsalvageable build with a live go-to-market deadline.
The platform I threw away in week one
Inherited an unsalvageable build with a live go-to-market deadline.
Source.One's first platform arrived from a subcontractor: an over-engineered microservices build with poor coding standards, and a product concept that forced buyers and suppliers through separate logins — an adoption killer in a market that transacts on WhatsApp.
The call: not recoverable inside a three-to-six month go-to-market window. So we didn't try.
Instead: WhatsApp as the front end, because it was already universal among buyers, suppliers and transporters. A CRM as an improvised back end. Custom middleware for messaging, algorithms and automation. Two-way conversational commerce, years before it was a category.
We replaced the improvised back end once it became the constraint, then shipped native buyer and supplier apps for the users who'd outgrown a chat interface. Every migration happened when the business needed it — not before.
ML with a P&L outcome
Freight estimates that stopped eating the margin
Cost-estimate error cut from roughly 19% to under 7%, nationally.
Freight estimates that stopped eating the margin
Cost-estimate error cut from roughly 19% to under 7%, nationally.
In industrial distribution, freight is quoted before it's incurred. Every point of error between the estimate and the actual cost comes straight out of a margin that is thin by definition — and across a national network of lanes, vehicle types and seasons, the estimates were running roughly 19% out.
Under 7% after the model shipped. That difference is margin recovered directly, on every movement, in a business where the whole game is unit economics.
It sat alongside a personalised minimum-price engine, real-time supplier price matching per order, and a reverse-auction freight quotation system that secured the lowest price for each vehicle movement.
Engineering leadership
Twenty-five engineers, then twenty
Restructured into three divisions and cut headcount while the business grew.
Twenty-five engineers, then twenty
Restructured into three divisions and cut headcount while the business grew.
Most engineering stories are about growth. This one runs the other way: the platform behind a ₹3,000 Cr business was built and run by 20–25 people, and I deliberately trimmed it to 20 while revenue kept climbing.
That was possible because of how the function was organised:
Merging the SDE and PM roles meant engineers owned product outcomes rather than receiving tickets. A separate architect track kept technical depth from being flattened by delivery pressure. AI Engineers were a standing division, not a side project.
Delivery ran on explicit must-have / good-to-have / nice-to-have prioritisation, held firmly. That discipline is why go-to-market windows were makeable and why cumulative technology spend stayed under $1M — 0.08% of revenue.
Range
I've dropped into unfamiliar businesses before
Depth at one company matters less than evidence I can learn yours quickly. Before Source.One I spent two years in a consultancy doing exactly that — a new domain every few months, architecture chosen per problem rather than mandated.
Digitised Sodexo's paper meal-voucher system; built a Kenyan smart-energy IoT product zero-to-one; launched GlobalCitizen's India platform for the Coldplay concert with a two-person team.
Retail Services' global ML-driven competitive pricing platform — billions of data points daily. Led an end-to-end AWS rewrite of a subsystem.
Azure disaster-management team: analysed a multi-region cloud outage and designed mitigation strategies.
B.Tech Computer Science, NIT Warangal. MS Aerodynamics & Computation, University of Southampton.
Next step
If the tech budget has become the story, that's usually a solvable problem.
Fractional CTO engagements, technology advisory, fixed-scope builds — and I'll consider the right full-time CTO seat.