Como é que a IA toma as decisões?

A plataforma não toma decisões pelo utilizador. Os modelos processam dados de mercado e geram sinais com base em padrões validados por backtesting. O utilizador vê o sinal, a métrica de risco associada e o histórico de precisão da estratégia, e decide o que fazer com essa informação.

Os dados da minha conta ficam visíveis para terceiros?

Os dados de conta e de carteira são cifrados em trânsito e em repouso. Não são partilhados com terceiros para fins publicitários. O acesso interno à infraestrutura é limitado a funções técnicas necessárias ao funcionamento do serviço.

A plataforma integra-se com a minha corretora atual?

O terminal aceita importação de dados de carteira através de ficheiros exportados nos formatos mais comuns, além de ligação direta nos casos em que existe suporte de API compatível. A lista de integrações disponíveis está detalhada na documentação técnica.

Preciso de conhecimentos técnicos para usar o terminal?

Não é necessário programar nem configurar modelos. A interface foi pensada para quem lê relatórios de investimento, mas não constrói algoritmos. Ainda assim, todos os termos técnicos usados nos sinais estão documentados.

Que histórico de dados é usado nos testes retroativos?

Cada estratégia é testada contra um conjunto alargado de dados históricos, abrangendo diferentes condições de mercado, incluindo períodos de queda acentuada e de recuperação. O período exato usado em cada teste é apresentado junto da estratégia correspondente.

NeutoTrade AI — data analytics dashboard for remote investment decisions

Data Analysis · Remote Investing

Investment decisions based on data, not emotion.

NeutoTrade AI analyzes markets in real time and tests each strategy against historical data before presenting it as a recommendation. Works in any browser, from any location.

Access the Terminal View Documentation

Live Analytics Dashboard: risk exposure per position, predictive signals pending review and historical accuracy of each active strategy, recalculated with each new market data cycle.

The problem

Manual analysis does not keep up with the speed of markets

—Reviewing dozens of indicators manually consumes hours that a remote professional rarely has available across time zones.
—Decisions made under emotional pressure ignore patterns that historical data has shown before.
—Generic analysis tools do not distinguish noise from signal in volatile markets.
—Without a record of backtesting, it's difficult to know whether a strategy worked through luck or consistency.

NeutoTrade AI replaces manual analysis with predictive models that process the same data, in the same way, at any time. Each recommendation arrives accompanied by its backtesting history, so that the final decision is always informed.

About the platform

Built for those who work outside of a fixed office

The NeutoTrade AI was designed for professionals who manage investments or business decisions from any location in Portugal or abroad. The terminal runs in any browser, without the need for local infrastructure, and keeps the analysis history synchronized between devices.

Development focuses on predictive models and backtesting, not decorative interface features. Each update to the analysis engine undergoes validation against historical data before reaching the user's account.

NeutoTrade AI — team analyzing market data in a remote work environment

Methodology

How each strategy is validated before reaching you

The process follows five fixed steps. No recommendation is presented without going through them all.

No.	Step	What happens
01	Data collection	Prices, volumes and macroeconomic indicators are collected from multiple sources at short intervals.
02	Backtesting	Each strategy is tested against historical data from different market cycles, including periods of high volatility.
03	Predictive modeling	The patterns validated in the backtest feed models that generate signals for the current scenario.
04	Risk Review	Each signal is accompanied by a risk exposure metric before being presented to the user.
05	Delivery	The recommendation arrives at the terminal with the accuracy history of the associated strategy.

Encrypted data in transit and at rest

Backtesting results reflect the performance of the strategy on the historical data used. Past performance does not guarantee future results. Therefore, each strategy presents the period and sample of data tested, visible before any decision.

Results

Four areas where automated analysis changes everyday life

Gains focus on consistency and speed of response, not promises of returns.

Risk reduction

Each recommendation includes risk exposure calculated before the decision, not after it.

Exposure calculated by signal

Scalability

The same analysis engine tracks one or several portfolios without losing processing speed.

Monitored portfolios without fixed limit

Real-time analysis

Signals are recalculated with each new market data cycle, not in weekly reports.

Continuous update

Auditable history

Each recommendation is recorded with the strategy and backtest that originated it.

Permanent registration per account

Use cases

How a remote investor uses the terminal in their daily lives

Scenario 01

Manage a portfolio across different time zones

The user opens the terminal in the morning, local time, and reviews the signals generated during the night. Each signal has a confidence level based on the backtest of the strategy and an already calculated risk exposure. The final decision — accept, adjust or ignore the signal — always remains with the user.

Dashboard · Active wallet

Pending signals3

Current exposure to riskModerate

Last data update4 min ago

Active strategies5

Scenario 02

Deciding on capital allocation in a small business

A manager without a dedicated analysis team uses the terminal to compare allocation scenarios before confirming a quarterly investment. The backtesting history of each strategy is available for consultation, which makes it easier to justify the decision to partners or external investors.

Panel · Comparison of scenarios

Scenarios under analysis2

Backtest periodMulti-cycle

Report exportAvailable

Shared accessActive

FAQ

Transparency about how AI works

How does AI make decisions?

The platform does not make decisions for the user. Models process market data and generate signals based on patterns validated by backtesting. The user sees the signal, the associated risk metric and the strategy's accuracy history, and decides what to do with that information.

Is my account data visible to third parties?

Account and wallet data are encrypted in transit and at rest. They are not shared with third parties for advertising purposes. Internal access to the infrastructure is limited to technical functions necessary for the operation of the service.

Does the platform integrate with my current broker?

The terminal accepts import of wallet data through files exported in the most common formats, in addition to direct connection in cases where compatible API support is available. The list of available integrations is detailed in the technical documentation.

Do I need technical knowledge to use the terminal?

No need to program or configure templates. The interface was designed for those who read investment reports, but do not build algorithms. Still, all technical terms used in signals are documented.

What historical data is used in backward testing?

Each strategy is tested against a broad set of historical data, covering different market conditions, including periods of sharp decline and recovery. The exact period used in each test is displayed next to the corresponding strategy.

Additional technical questions: consult technical documentation.