There was a famous French artist and futurist Jean-Marc Côté who tried to imagine the world 100 years ahead. These are impressive works by a man who understood scientific trends quite well.

But even these works, if you look closely, entirely consist of things that had already been invented and only acquired some yet non-existent technical form.

Take for example control exclusively by wires or flights? That means there will be airplanes. The logic of scientific aspirations is correct, but to imagine exactly how it will look and especially how people will use these gadgets of the future is, of course, an absolutely incredible task.

For example, the classroom illustration. The understanding that digitization would win existed, but the image of a computer into which books are thrown like into a meat grinder and it produces analog signals is, of course, very far from the reality of what was eventually invented.

And I emphasize — this is still the view of a person who tried to think deeply about it.

The average person for a long time thought that the big machine of the future would be 1,000 horses in one powerful harness :)

And Here Begins the Most Interesting Part

When creating our AI, we essentially found ourselves in a similar situation, or rather, we are faced with something clearly completely different!

You will not find the usual technical analysis here.

No endless triangles, rectangles, arrows, levels, trendlines, or other sacred symbols of trading folklore.

That is precisely why we often seem like outsiders at the great celebration of trading culture.

The reason is simple.

We try to start with research rather than belief.

What Is a Scientific Truth?

The main goal of our blog is to introduce traders to our system and our approach to market analysis.

At first glance, everything should be fairly straightforward:

• there are results,
• statistics,
• verifiable metrics,
• and public accounts.

In other words, there are objective indicators that should at least deserve attention.

However, something else regularly surprises us. We constantly observe how aggressive marketing from various “strategy creators” and “success sellers” often becomes far more visible than real, verifiable systems.

All it takes is opening almost any trading-related advertising feed. Right before writing this article, we came across the following headline: “$10 to $20,800 in 5 days”. And statements like this have practically become normal.

This article should have been written among the first ones, because it describes the very principle of how we view the market.

Usually, a chart is perceived as a simple two-dimensional line: price moves up, down, or stays in a flat. However, this view greatly oversimplifies reality. In fact, any market chart is only a projection of a much more complex structure.

This is exactly what we are trying to show in our 3D video.

Why a Regular Chart Is Only a Slice

A small departure from the usual format — a bit of reflection 😉

What is especially telling — we do not use traditional technical analysis when presenting ORA AI trades.

Here is the trade. Here is the chart. Here is the result.
And also — overall limits and edge buffer.

Simple, right? 🙂

And yet, this simplicity often вызывает resistance.

Because many traders are used to thinking that things must be “MUCH more complex.”

How can one trade without geometric constructions? 😏

Let me say something as an engineer with a strong mathematical background — and I’ll try not to offend anyone…

The idea that geometric lines, shapes, and patterns — because they come from mathematics — must therefore inherently “work”…

That by drawing complex constructions, one somehow gets closer to results…

This is not how it works.

In the public domain, it is extremely difficult to find systems that simultaneously demonstrate:

• thousands of trades
• a consistently high win rate
• a stable profit factor
• multi-pair trading

• long-term operational history

ORA demonstrates all of these characteristics at once.

These are not assumptions — these are facts.

Back in college, our physics professor used to repeat quite often: it doesn’t matter what result you obtain if the margin of error is not calculated alongside it.

Many years have passed, but to this day I consider this idea — expressed in a very concise form — one of the key insights in understanding how to evaluate any result.

Most importantly, this principle provides a solid safeguard against errors in evaluation — and not only mathematical ones.

A simple example: imagine measuring a distance using only a one-meter ruler without any centimeter or millimeter markings. Anything below one meter would be measured with enormous error. Estimating by eye introduces a large uncertainty — plus or minus 10 or even 15 centimeters.

If you attempt to measure kilometers with such a tool, the problem becomes even worse. Terrain irregularities, curves, repetitions — all these objective factors introduce additional inaccuracies that are very difficult to eliminate.

This is the core problem of all measurement.

This post serves as an announcement of an important milestone.

For quite some time, we have been frequently asked whether there are plugins or integrations available for platforms such as TradingView and MetaTrader 5. However, to be completely transparent — our priority has never been to launch something quickly for the sake of monetization.

Our primary goal has always been something we would want for ourselves: confidence — as much stability and clarity as possible when working with our AI.

Imagine that there exists a system capable of predicting market direction with a probability exceeding 90%.

And imagine that this claim is supported by fully transparent, verified statistical data.

For now, we are not even talking about our AI (we will come back to it shortly).

We are referring to a hypothetical system that, over tens of thousands of trades, demonstrates a win rate above 90% — or even above 95% — in a consistent and verifiable manner.

It is important to highlight the following.

When we asked systems like GPT and Grok whether such systems exist, they were unable to recall any examples within their extensive knowledge bases.

The question was simple:

How can you trust something you don’t fully understand?
And why assume that it actually works?

These questions are rarely asked directly, but they are almost always there in the background when someone first encounters what we are doing.

We don’t disclose everything, and to be fair, we don’t think everything needs to be disclosed. In practical terms, results tend to speak louder than explanations. Still, there are a few points worth sharing.

How systems are usually evaluated

As mentioned earlier, our primary background is not trading, but construction engineering. This is exactly why our perspective on markets — coming somewhat from the outside — may be both different and, we hope, useful. And here’s why.

In engineering, the central principle is responsibility.

Any statement, assumption, or conclusion must be grounded in calculations performed in strict accordance with established standards and frameworks.

The reason for this is quite straightforward.

Today, financial markets host a vast number of trading strategies, along with an equally wide spectrum of opinions on what defines success — from simple, rule-based approaches to highly complex systems operated by professional teams using advanced analytical frameworks.

In a way, this diversity — often containing fundamentally contradictory views — reflects the nature of the market itself: a system that can be described as chaotic in the classical sense.

This form of chaos is not intuitive. Any attempt to formalize it quickly reveals a core limitation: at the moment of decision-making, outcomes tend to converge toward a probabilistic baseline — effectively close to 50/50. Either the market continues in the expected direction or it does not.