Smarter wealth for the self-employed
Brisqella uses predictive AI to decide when and how much to invest, turning irregular freelance income into a disciplined, automated savings strategy. No manual timing, no spreadsheets, no guesswork.
Brisqella uses predictive AI to decide when and how much to invest, turning irregular freelance income into a disciplined, automated savings strategy. No manual timing, no spreadsheets, no guesswork.
Brisqella was built around this specific pattern of work. Rather than asking freelancers to commit to a fixed schedule, the platform adapts to actual cash flow, optimising entry points as funds become available and reducing the time spent second-guessing the market.
Three components work together continuously, analysing data, identifying entry points, and managing exposure so that decisions are made with precision rather than instinct.
The system ingests market and macroeconomic data continuously, building a current picture of conditions rather than relying on stale snapshots.
Instead of investing a fixed amount on a fixed date, the model identifies favourable entry windows and adjusts contribution size accordingly.
Exposure is adjusted in response to volatility, with built-in limits that prioritise capital stability over chasing short-term gains.
Every decision the platform makes follows the same repeatable process, so you always understand the logic behind an action taken on your behalf.
Market data, pricing history, and your available balance are gathered continuously to keep the model's view current.
The engine evaluates conditions against historical patterns to estimate favourable entry points and appropriate position sizing.
Once conditions align with your risk settings, contributions are placed automatically, leaving you free to focus on client work.
Brisqella was designed around one observation: most investment tools assume a steady monthly salary. Freelancers and contractors do not work that way, and shoehorning irregular income into a fixed plan often leads to missed opportunities or unnecessary risk.
The platform instead treats each incoming payment as a decision point, applying the same predictive logic consistently so that growth is pursued with discipline rather than emotion.
The underlying engine is the same in both cases. What changes is the risk profile and the time horizon applied to the recommendation.
A larger-than-usual invoice is paid, leaving a lump sum that would otherwise sit in a current account. Rather than investing it all at once or waiting indefinitely, the model spreads the entry across several favourable points identified over the following weeks.
Funds set aside for an annual tax bill still need to be accessible, but sitting entirely in cash means they lose value in real terms. Brisqella applies a lower-risk predictive model to this reserve, aiming for modest, steady growth rather than aggressive returns.
Account and transaction data are encrypted in transit and at rest. Access to your data is limited to the systems required to generate recommendations and execute transactions, and nothing is shared with third parties for marketing purposes.
Your cash flow patterns and risk preferences are used solely to calibrate the predictive model to your circumstances. Aggregated, anonymised data may be used to improve the underlying models, but it is never linked back to an individual account.
The model weighs current price trends, historical volatility, and your risk settings before recommending an entry point. During periods of elevated volatility, the system is designed to reduce position size or pause contributions rather than force a decision, prioritising capital stability over speed.