The tools that built retail systematic investing in the West share an assumption: that the user can write code in English. QuantConnect expects Python or C#. TradingView expects Pine Script. AmiBroker expects AFL. For the United States, that assumption excludes fewer people than you might think. For India, it excludes almost everyone who is actually opening a demat account today.
The arithmetic of exclusion
Start with the ratio, and let us be precise about it: the exact figure depends on how you count. India has on the order of 5.4 million professional software engineers (IBEF). The investing population is either ~130 million unique investors (NSE, by PAN, April 2026) or ~216 million demat accounts (CDSL and NSDL, end-2025), depending on whether you count people or accounts. Divide it through and professional coders are a low-single-digit share of investors: somewhere between one in twenty-four and one in forty. This is an estimate, not a survey. Developer counts run far wider once you include everyone who has ever opened a code editor: GitHub alone counts 21.9 million India-based accounts, most of them students, hobbyists, or one-off sign-ups, not people who could sit down and write a working Python backtest. Even on that generous count, coders remain a minority of investors: at most one in six.
Now layer on language. The strategy-coding world runs in English, and India ranks 74th of 123 countries and territories on the 2025 EF English Proficiency Index, in the “low proficiency” band. The 2011 Census recorded only about 10.6% of Indians reporting any English at all, and a far smaller fraction speaking it fluently. A platform that requires reading English documentation and writing English-keyword code is not “a bit harder” for most Indians — it is a closed door.
Finally, look at where growth is coming from. More than 60% of new demat accounts in 2024 were opened beyond the metros, and the median NSE investor is now around 33 years old. The next hundred million investors are disproportionately younger, in smaller cities, and less likely to have a computer-science background than the early-adopter cohort in Mumbai and Bengaluru.
Put the three together and the conclusion is not a preference. It is a constraint: in India, code-first systematic investing tools are structurally limited to a tiny, non-representative slice of the market.
Visual is not “dumbed down” — the evidence
There is a lazy assumption that no-code means less capable. The human-computer interaction research says otherwise for the population that matters here: novices.
In a peer-reviewed quasi-experiment, Weintrop and Wilensky (2017) compared isomorphic block-based and text-based programming introductions and found the block-based group showed greater learning gains and higher continued interest in computing. A 2025 meta-analysis of K-12 studies reached a consistent conclusion: visual, block-based environments carry an upper-medium effect on learning outcomes, strongest for novices, and reduce the syntax-error friction that stops beginners before they start.
The point is not that visual is a toy. It is that visual programming removes a barrier — syntax and English keywords — that has nothing to do with whether someone understands markets. A trader in Indore who understands momentum perfectly well should not be blocked from expressing it by a missing semicolon.
Where saral.money fits
saral.money is visual-first by design. A strategy is built by connecting nodes: a universe such as Nifty 500, filters like PE < 20, ranking rules, position sizing, an output, assembled into a pipeline you can see. There is no Python, no Pine Script, no AFL. And the AI assistant lets a user describe a thesis in plain language and receive an editable strategy flow in return, not a black box, but the same rule nodes you can open, read, and change.
The honest limits, stated directly:
- The interface is in English today. Vernacular support, Hindi, Marathi, Tamil, and others, does not exist yet. We would rather say that plainly than imply a reach we do not have.
- No-code lowers the barrier to building; it does not lower the barrier to understanding markets. A visual editor will happily let you build a bad strategy. What it does is make the good ones reachable without a coding background — and make every rule visible so you can learn from it.
The goal is narrow and real: let the person who has the market insight express it, test it, and run it — without first having to become a programmer.
What to try next
Open the strategy builder and assemble a simple momentum strategy by connecting nodes: no code, no syntax. Then read how to backtest it properly so the result means something. The whole idea is that the only skill you should need is an understanding of the market — not of a programming language.