How I Let AI Read a Chart Screenshot and Predict a Trade — It Got It Right

Business News & Trends
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Over the past few weeks, I stumbled upon the ability of AI to analyze screenshots — almost by accident.

That small discovery opened the door to something far more interesting: could a simple image of a trading chart be enough for an AI to generate a real-time, actionable trade plan?

So, I decided to put it to the test.

The Setup

  • Instrument: Nifty50 Futures
  • Chart Type: Second-based intraday chart
  • Indicator: Volume Profile (Visible Range)
  • Platform: Screenshot taken directly from a charting tool

Rather than running a backtest or building out a full algo, I kept it simple:
Today I uploaded a screenshot of my chart to an AI platform capable of visual data interpretation.

What Happened

To my surprise, the AI didn’t just “see” the image — it understood it.

It recognized key structural elements of the chart, including:

  • Price action context
  • High-volume areas
  • Possible demand/supply zones
  • Likely points of inflection

And based on that, it generated a coherent, real-time intraday trade plan — purely from what was visible on the chart.

How It Works (Technologies Involved)

What made this possible wasn’t just one tool, but a combination of advanced technologies working seamlessly in the background — all triggered by something as simple as uploading a screenshot:

  • OCR (Optical Character Recognition) to extract price, time, and volume levels from the image
  • Computer Vision to interpret the layout and structure of the chart
  • Multimodal Large Language Models (like GPT-4 with vision) to combine that visual data with contextual trading knowledge and generate strategic insights

This wasn’t just “reading a chart” — it was context-aware market interpretation based on the same visual data a human trader would use.

The Outcome

The AI highlighted the key price zone to watch.
A few hours later, the Nifty responded almost exactly at those suggested level.

In the full-day chart I’ve attached below, you’ll see a blue line marking the time when the screenshot was analyzed by AI (timestamp on the output screenshot). The subsequent price action respected the suggested levels, reinforcing the accuracy of the AI-generated plan.

There was no data mining, no hindsight bias — just a clean chart and a real-time suggestion that held up.

Why This Matters

This isn’t about high-frequency trading or opaque black-box systems.

This is about:

  • A retail-accessible, no-code workflow
  • Built with publicly available AI tools
  • Using everyday chart visuals
  • And delivering real, actionable clarity

It’s a practical example of how AI can augment trading intuition — not replace it, but enhance it by combining speed, structure, and contextual pattern recognition.

What’s Next?

I believe this is just the beginning of a new kind of trading workflow — where chart screenshots and AI can work together to support faster, smarter decisions.

Format of Chart Setup Sent to AI for Analysis
Format of Chart Setup Sent to AI for Analysis2459×1241 178 KB

Intraday Trade Plan Generated by AI based on the screenshot Sent
Intraday Trade Plan Generated by AI based on the screenshot Sent880×941 96 KB

:pushpin: Disclaimer:

The content shared in this post is for educational and research enhancement purposes only. It does not constitute financial advice or a recommendation to buy or sell any financial instruments. Always conduct your own analysis or consult a qualified advisor before making any trading decisions.

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The explanation is good. I would really like to read how these analyses helped you trade and whether you actually took a trade based on the AI suggestions. If yes, then was it intra or positional and would you do some more analysis for the exit?

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To clarify, this was a real-time intraday analysis generated around 1:15 PM, as mentioned in the original content. The objective wasn’t to signal a live trade, but rather to highlight how a structured, observational approach can help uncover intraday bias and map out potential trade scenarios as the session progresses.

While I didn’t act on this particular setup—since I’m currently aligned with a different trade plan and broader strategy—the analysis itself was shared as part of an ongoing experiment to test real-time market reading without the advantage of hindsight. The true outcome, as expected, only became evident by the session’s close.

I fully understand the sentiment many have around the idea of “put your money where your mouth is”—it’s a fair expectation in trading circles. But in this case, the goal was slightly different: to focus more on process than profit. There’s immense value in training oneself to observe, interpret, and document price action in real time, even without taking a position. It sharpens intuition, builds confidence, and over time, contributes to more decisive execution when the setup truly aligns with one’s plan.

Going forward, I’ll continue these observational studies, and where applicable, start layering in analysis for possible exits when a trade setup reaches that level of maturity. Trading is a journey after all—and not every insight needs to be monetized immediately to be meaningful. Sometimes, the quiet work done behind the scenes is what lays the foundation for consistent performance later on.

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Well my intention was to understand if there was a specific risk-to-reward involved and AI was really helpful in giving good insights. I am working on something similar i.e. coming up with a prompt to give out confidence scores based on the inputs which will comprise of user query, 5m OLHC and Option strike prices.

Anyway, please keep on sharing your observations as these are good reads for me to apply.

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Are your ideas centered around sending raw data for analysis, or are they aligned more with the approach outlined in the main thread—using something simpler, like a one-click screenshot directly from the chart?

The idea is that sending a straightforward screenshot directly from the chart can be a far more user-friendly and widely adoptable method.

While this approach isn’t entirely new, it still feels underexplored—and it carries strong potential. A single click to capture and interpret market structure or trade setups could be a game-changer—not just in terms of speed and accessibility, but also in everyday usability for traders.

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Sending an image means to use an image processing model which would process and get data which then goes to an analysis model to analyze the data. Ofcourse with ChatGpt or other clients, it’s all abstracted and the user doesn’t know what is happening in the backend. Well I am going step by step so currently it’s raw data with a custom-built prompt to get a response. Image processing would come later but is not needed at the moment atleast for what I am working on.

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@PravinJ ,

It will be interesting to see which online trading platform brings up such features in the industry.

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Hello @Brishide,

So, 1–2 trades in a short window and you’ve found the “elixir” of trading? Nah, mate — that’s not how markets work.

Here’s why:

(1) Time Samples:
Short-term predictions prove nothing. In bullish or good-news phases, even bad calls can look genius. A strategy only matters if it survives multiple market cycles — that means years, not days.

(2) No Decision-Making Framework:
If you don’t have a structured decision-making system of your own, your so-called “edge” will quickly normalize. What seems special now will be absorbed by the market, and you’ll be left with the same diluted alpha as everyone else.

(3) Small Sample Size:
A few trades mean nothing. To even begin evaluating a strategy, you need at least 1,000 trades — only then can you measure win rate, expectancy, drawdowns, and variance.

(4) Survivorship Bias:
You’re looking at the trades that worked and ignoring the ones that will go the other way. Markets don’t reward selective memory — they punish it brutally.

(5) Emotional Fragility:
Two wins can make you overconfident, biased.

(6) Why AI Can’t Do It For You:
AI is great at crunching data, but markets aren’t just data — they’re human psychology, liquidity flows, manipulation, and randomness. AI can optimize backtests, but it can’t account for regime shifts, black swans, or how you will execute when real money is on the line. Blindly following an AI signal without discretion is like handing the steering wheel to a GPS during a landslide — it doesn’t know when the road has changed.

In short: what you’re doing right now is shallow and amateurish. It’s fine for fun, but far from conclusive.

If you’re serious, test across large sample sizes, multiple market cycles, and stress test your strategy under worst-case conditions. Otherwise, you’re declaring victory in a warm-up lap.

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Rightly said that AI is good at crunching data because it works on past data but it does help in insights where you can get to patterns. If programmed correctly, it can predict a few events. Look at BlackRock’s cutting-edge AI Alladin. It has so much power and data that it is said that it predicted pre and post 2020 and helped investors.

Ofcourse you cannot get the same results with Chatgpt but with the traditional approach, you can atleast get the conviction right to trade with a better probability :slight_smile:

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@hachiko Well Fyers has already launched their FIA on chatgpt. I had a specific post here in the community where I had mentioned how to get a small MCP to link to your dhan account and integrate with Claude for analysis. Dhan has started with Fuzz but not sure when it will be released. I feel they need to work on other things before they try to swim in the AI ocean.

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Marketing gimmick.

That is more like a excel sheet with 20,000 data points, each have their own weightage assigned which is based on market conditions, and compiling those weightage will throw up a direction.

Quant AMC is also building something like that.

Even I am working on an ongoing project that fetches data from economic APIs and market APIs, but that is more like a toy because it is built in LibreOffice, so I have a little bit of sense what’s going under the hood.

I still maintain the stance that nothing can beat value investing, quality smallcap & microcap investing and discretionary trading.

If you can master yourself and trust you to execute strategies well, you’ll outperform any overhyped kaala-pathar by several times, it’s just that the World won’t know it because you aren’t selling anything and hence no marketing of it.

And I don’t trust crony bhai with a single penny, if Blackrock found another Indian partner, I would have gotten some Alladin action, albeit overhyped.

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@thisisbanerjee At the moment, given all the tools like ChatGPT, perplexity, etc, I agree with you that personal trading/investing beat everything. However, I also believe that AI can be an assistant that provides insights to strengthen your conviction. I believe in AI-assisted human trading/investing :slight_smile: as it will help in improving the probability.

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Assisted is the keyword, that you have nicely grasped while many others struggle to.

Kudos to you for that. With this attention to detail, you could make it big in life.

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Right, FIA is integrated within charts. Not sure whether AskFuzz will be a separate domain or will get integrated within charts.

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Hype. No value addition to any trading strategy. No direct monetary benefits.

ChatGPT already outperforms on all metrics. Perplexity Finance does unparalleled screening. (TradingView screener is the best though.)

Ease of life mostly.

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