Trading technology/ SOLERON

One market.
Four distinct approaches.

Review each bot’s reported results alongside its costs and drawdowns.

From gross profit to net result

Reported maximum drawdown

Each bot is shown for its own reporting period.

₮ = USDT · $ = US dollars. All amounts in this atlas are denominated in USDT.

Reported net profit is after exchange trading and funding fees; investor-specific contractual costs are excluded. The report does not explain the drawdown methodology in detail.

Charts reflect dated reports supplied by the company, rather than current live account data. Source coverage and methodology are explained under “Source notes”.

Technology

Infrastructure connecting market data to trading decisions

SOLERON develops automated trading bots that operate on crypto exchanges. The documented architecture combines order-book data with AI-supported analysis and order management.

The model architecture describes LSTM, Transformer and reinforcement learning components. This does not imply that every component operates identically across all bots.

DATA

Liquidity alongside price

Order-book imbalance and the rate of change in market depth provide additional decision inputs.

MODEL

Assessment by market regime

The documented LSTM, Transformer and reinforcement learning architecture is intended to assess different market regimes.

EXECUTION

From signal to order

Adaptive order routing and a risk budget for each trade support execution on the exchange.

These mechanisms are described in the sources. No separate analysis has been provided to measure each mechanism’s contribution to reported profit.

Source: KINGSBOT_v10_Technical_Deck_EN, pp. 3–7.

Bots

Four distinct strategy profiles

Explore strategy behaviour on a chart
HOW THE MECHANISM WORKS

Bots interpret market moves differently

Mean reversion considers deviations from a reference level; momentum considers an ongoing directional move. Compare both approaches and an adverse scenario.

Source: Institutional Performance Report, p. 1. Illustrative visuals; these are not actual trade or return charts.

Mr-Crypto-AI

Mean reversion

18 February – 16 August 2026

MRCryptoAI5-2-0

Trend and momentum

6 May – 14 August 2026

MRCRYPTO-AI-Quantum

Aggressive, high beta

19 May – 14 August 2026

Quantara

Quantitative, directional

28 March – 15 August 2026

Dates indicate the periods covered by the available reports. Strategy classifications are taken from page 1 of the institutional report. These descriptions do not reveal bot-specific model thresholds or parameters.

Risk approach

Risk controls within the trading process

Explore an illustrative stop adjustment
HOW THE MECHANISM WORKS

Decisions continue after a trade is opened

This example shows a stop moving towards the entry level as a long position moves favourably.

Source: Technical Deck, pp. 7 and 9. Illustrative visuals; these are not actual trade or return charts.

Position sizing for volatility

The documents also describe dynamic position sizing, VaR and correlation controls. The aim is to reassess exposure as market conditions change.

Losses remain possible

A breakeven stop does not eliminate losses because fees and execution conditions still matter.

These mechanisms do not eliminate losses. Leverage, market movements, order execution and exchange operations can lead to substantial losses.

Read the risk and cost disclosure

Source: Technical presentation, p. 7. Reported drawdowns do not set a limit on future losses.

Operating model

Trading capital stays on the exchange

User

Keeps trading capital within the exchange environment.

Trading capital

Exchange environment

Account infrastructure and order execution.

Trading instruction

SOLERON

Develops strategies and trading technology.

SOLERON does not directly receive or custody users’ trading capital.

Technology access

Strategies and trading infrastructure are accessed through the exchange environment.

Trading terms

Exchange access, trading permissions, reporting and exit terms are clarified before activation.

Risk and cost disclosure
Company

Technology evolving under SOLERON

The technology developed under the King’s Bot AI name is continuing under the SOLERON brand. An ADGM holding company, AI technology and crypto trading companies in Dubai, and a Dubai-based marketing company serving the group are being established.

Transfer of the technology to SOLERON is planned after incorporation. The formation process does not mean registration is complete or that an operating licence has been granted.

ADGM holding companyUnder formation

AI technology company

Dubai

Crypto trading company

Dubai

Marketing company

Dubai

Planned group structure. This diagram does not confirm completed ownership arrangements or operating authorisation.

Leadership

Hakan Sedefçi

CEO

Evren Eter

CTO

İsmail Evren Altuntop

COO

Abdullah Ağartıoğlu

CMO

The company reports a distributed team of approximately 60 people. The structure and roles reflect information provided in September 2026.

On Instagram

SOLERON in action

Short brand films from @solerongroup. Watch on Instagram and follow our latest posts.

Meeting

Let us review the strategy and trading terms together

Discuss the technology, bot reports, exchange access and commercial terms in one meeting. Minimum allocation, exit terms and contractual costs should be clarified before capital is allocated.

Download the meeting preparation note

The preparation note is saved to your device. It does not submit a meeting request.

What does this atlas show?

Bot names, strategy classifications and reporting periods come from the available company documents. The waterfall chart separates gross profit, trading fees, funding and reported net profit. The drawdown chart shows each bot’s maximum drawdown during its own reporting period. Periods and capital bases differ; these charts are not a like-for-like performance ranking.

The institutional report describes the results as “audited”, a designation accepted by the company. The supplied documents do not identify the auditor or specify the scope of the audit.

The data here reproduces company reports and does not constitute independent verification of raw trade records. For Quantara, the component total differs from reported net profit by ₮1 USDT.