¿Cómo se protegen los datos financieros y de conexión?

Las conexiones con exchanges y brokers se realizan mediante claves de API con permisos restringidos a lectura y operativa de compra, sin capacidad de retirada de fondos. Los datos se almacenan cifrados y el acceso al panel requiere autenticación independiente de las credenciales de cada plataforma conectada.

¿Qué plataformas admite la conectividad por API?

La integración se realiza mediante claves de API estándar compatibles con los principales exchanges y brokers que ofrecen este tipo de acceso. Antes de activar la conexión, el sistema valida los permisos de la clave y confirma que no incluye capacidad de retiro.

¿Cómo decide el sistema cuándo fraccionar una entrada de Smart DCA?

El motor compara la volatilidad reciente del activo con su rango histórico. Si la desviación supera el umbral configurado, divide la aportación programada en tramos más pequeños distribuidos en un periodo corto, en lugar de ejecutarla de una sola vez.

Artificial intelligence for capital decisions

Predictive analysis and automated cost averaging for those who cannot monitor the market daily

Figiri Tigelo processes market data in real time and executes a volatility-adjusted Smart DCA strategy, designed for freelancers and independent investors who manage their capital between projects.

Optimize my strategy View technical demo

What you would see in the control panel

Current exposure per asset, deviation from the planned inflow schedule and estimated risk level for the next purchase cycle, recalculated each time new market data arrives.

The problem

Too much data, not enough time to interpret it between one project and the next

Those who are self-employed usually allocate irregular income to investment, but lack the time—and often the technical training—to follow volatile markets continuously. The usual result is to decide on impulse, postpone entries or abandon the strategy after the first falls.

Volume of information greater than what a person can review daily without spending hours on it.
Capital inflows decided by intuition rather than quantifiable criteria.
Lack of a buying calendar that adapts to volatility rather than ignoring it.
Difficulty distinguishing market noise from strategy-relevant signals.

Volume of market signals processed against which a manual review can cover in a daily session.

Each bar represents a block of data (price, volume, volatility, correlation) that the engine evaluates continuously.

The solution

An analytics engine that converts market data into concrete input decisions

Figiri Tigelo combines automated data analysis with a Smart DCA optimization engine. It does not replace the investor's judgment, but it reduces the emotional and manual component of deciding when and how much to contribute.

Automated analysis

The system ingests prices, volume and volatility metrics of the selected assets and normalizes them into a comparable format, without manual intervention on your part.

Risk mitigation

Contributions are distributed according to the volatility detected, reducing the concentration of entries in times of high uncertainty and adjusting the size of each purchase.

Real-time insights

Each price update recalculates the recommended position, so the strategy reflects current conditions and not a fixed plan defined months ago.

Technical note: The input optimization engine weights moving averages, volatility bands and historical deviations to decide whether a scheduled contribution is executed on its original date, brought forward or divided into smaller tranches.

How we work with data

A platform designed for those who review their portfolio between tasks, not full time

Figiri Tigelo was born to fill a specific gap: that of those who generate income irregularly and want that capital to work without becoming a second occupation. The system documents each recommendation with the data behind it, so the reasoning behind an entry or risk adjustment can always be reviewed.

We don't offer guaranteed predictions or promises of profitability: we offer a consistent, traceable, 24-hour analysis process, which reduces the time a person needs to spend manually monitoring the market.

Figiri Tigelo team working on developing predictive analytics engine

Methodology

From raw data to an actionable recommendation, in three phases

Process transparency is part of the product: each recommendation can be traced back to the data and model that generated it.

Data ingestion

The system collects prices, volume and volatility metrics of assets configured through connections to market sources, with an update frequency according to the type of asset.

Predictive modeling

The data is processed with statistical models that estimate probable ranges of movement in the short term and detect conditions of anomalous volatility compared to the historical behavior of the asset.

Actionable recommendation

The engine translates the result of the model into a concrete input recommendation: execute, delay or split the programmed contribution, along with the justification for that decision.

Representation of the data flow: market source → normalization → predictive model → Smart DCA engine → recommendation with registration of the applied logic, visible in the control panel.

Practical application

Three common situations between freelancers and independent investors

Portfolio rebalancing without manual tracking

When the allocation between assets deviates from the defined objective, the system indicates the imbalance and proposes the contribution size necessary to correct it in the next cycles, instead of requiring a periodic manual review.

Configurable deviation threshold before generating an alert.
Progressive adjustment, not sudden one-time reassignments.

Strategic entry points in volatile markets

Instead of contributing a fixed amount on a fixed date, the input optimization engine evaluates recent volatility and distributes the contribution in tranches when it detects unstable market conditions.

Reduces exposure to buying the entire amount at a specific price peak.
Maintains the original schedule when volatility is low.

Automated capital growth between projects

For those who receive income irregularly, the system can be programmed to allocate a percentage of each collection to the Smart DCA strategy, without the need for manual intervention in each income.

Recurring or one-off contributions, depending on liquidity availability.
History of contributions and their justification available at all times.

Frequently asked questions

Common technical questions before starting

A more complete review is available on the FAQ page.

How is financial and connection data protected?

Connections with exchanges and brokers are made through API keys with permissions restricted to reading and purchase operations, without the ability to withdraw funds. Data is stored encrypted and access to the dashboard requires separate authentication of each connected platform's credentials.

What platforms support API connectivity?

The integration is done using standard API keys compatible with the main exchanges and brokers that offer this type of access. Before activating the connection, the system validates the permissions of the key and confirms that it does not include withdrawal capacity.

How does the system decide when to split a Smart DCA entry?

The engine compares the asset's recent volatility with its historical range. If the deviation exceeds the configured threshold, it divides the scheduled contribution into smaller tranches distributed over a short period, instead of executing it all at once.