Company
Two founders. Direct accountability.
Founded by Nithish Singh in Hosur, Tamil Nadu. One leads engineering, one leads the relationship. Both stay through deployment.
The founder
Nithish Singh
Founder, Doing AI
“The capability is available to everyone now. What separates the companies getting value from it is whether it gets built into how the business actually runs — wired into existing systems, tested against real volume, and supported once it is live. That is the work we chose to do.”
Doing AI is a two-founder team: one leads engineering, the other growth and client relationships. You deal directly with the people writing the code, from the first conversation through deployment and beyond.
A team this size is a fair thing to ask about, so we answer it directly. Everything we build runs in your accounts, on your infrastructure, fully documented. Your systems and your data remain accessible independently of us, and continuity is written into the agreement rather than left to trust.
Who you get
The people who do the work.
Everyone listed here works on your build. Nobody is listed who does not.
Nithish Singh
Founder — software architect
Six years building the kind of system this company sells — ERP and procurement platforms carrying OEM and supplier workflows, data pipelines at Comcast, retail and CPG analytics at NielsenIQ. The person who writes your code is the person who remains accountable once it is live.
Software architect at Adidev Industries in Hosur since 2023, where the work is manufacturing: ERP and procurement systems carrying OEM–supplier workflows, order lifecycle, sourcing and analytics — architecture, development oversight, QA governance, deployment and delivery, owned end to end rather than handed along. The invoice that disagrees with the goods receipt note, on the front page of this site, is not an illustration picked at random. It is the job.
Before that, data platforms: Comcast's XRM analytics through Tulasea and UST, building the pipelines that pulled scattered sources into one place. Before that, two years at NielsenIQ in Chennai on retail and CPG data — market segmentation, a sales forecasting model, the drivers of brand loyalty. Before that, network engineering at GEE VEE FAB in Hosur, automating monitoring and maintenance in Python until most of the manual work was gone. Computer science engineering at Adhiyamaan College, Hosur.
Shipped along the way, among others: procurement tracking and supplier follow-up for an automotive manufacturer, student admission and onboarding for a global education group, a reporting warehouse and reconciliation engine feeding that group's finance team, an internal chatbot, and a booking app that replaced a spreadsheet. Clients are unnamed here for the same reason they are unnamed everywhere else on this site — the agreements make that their call, not ours. Different industries, one task in different clothes: find the manual step between two systems that should already be talking to each other, and remove it.
Doing AI started from a complaint I kept hearing. Companies were paying for AI strategy and getting slides back: a set of recommendations, an implementation roadmap, and no working software at the end of it. The technology was ready. What was missing was anyone willing to build the thing, wire it into what the company already ran, and still be there when it broke on an ordinary Tuesday. So the company is built the other way round. Scope and price are fixed before anyone writes code, the first system goes live in weeks rather than quarters, and it runs inside the tools your team already opens. If I cannot see the path to production on the first call, I say so on the first call — before you have paid for anything.
Billgill Immanuvel
Co-Founder — growth, and usually your first call
Eight years in growth at BYJU'S, GrowthSchool and Jain Online. He has run these systems from the buyer's side, which is why he can usually tell on a first call whether a workflow is worth automating or simply worth deleting.
Eight years across three high-growth companies. At BYJU'S he worked customer acquisition and business development, close enough to the sales floor to learn how a customer base is actually built rather than described. At GrowthSchool he scaled growth across markets — large-scale performance operations, acquisition funnels, and the experimentation needed to tell which changes moved a number and which only looked like they had. At Jain Online the remit widened again: growth strategy, performance marketing, automation, CRM, lead management, analytics, customer journeys, partnerships and market expansion.
Running all of that at once teaches the same lesson repeatedly. As a business grows, so does its overhead. More customers mean more processes; more leads, more follow-ups; more teams, more coordination; more data, more decisions. Most companies answer with more people and more tools, and end up paying for the coordination instead of the work.
He leads growth, business development, client relationships and expansion here, and he is usually the first person you speak to. His test for any build is the one the whole company applies: does it fit the way the business already works, or does it ask everyone to work differently to suit the software? The second kind gets bought, praised, and quietly abandoned.
Two people is a fair thing to ask about, so here is the answer in advance. Everything we build runs in your accounts, on your infrastructure, documented — not locked inside ours. Your systems and your data stay reachable whether or not we are, and continuity is written into the agreement rather than left to trust.
The goal
The models are ready. The software around them is the work.
Most organisations already have access to capable AI. The difficulty sits everywhere else: the data a system reads, the applications it writes back to, who is allowed to approve what, the exceptions that still need judgement, and the accountability that starts the moment real work depends on it. That is not a model problem, it is an enterprise software problem, and it is the same problem in every sector — the vocabulary changes and the shape does not. That engineering is what we do, and we do it from inside the operation: an invoice that disagrees with a goods receipt note is not an illustration here, it is Tuesday. The models will keep changing. Governed software that people can be held to will not.
Continuity
Everything runs in your accounts, on your infrastructure, documented — not locked inside ours.
Reachability
Your systems and your data stay reachable whether or not we are.
In writing
Continuity is written into the agreement rather than left to trust.
How we hold it
Four commitments.
Engineering-led delivery
Each engagement produces working software running in front of your customers and your team.
Integrates with your existing stack
Your CRM, your spreadsheets, your internal tools. We build into what you already run.
Your data stays yours
Governed, auditable, and never used to train external models.
Weeks, not quarters
The first system is scoped, built and in production in four to six weeks, at a price agreed before anyone writes code.