A quant desk for your firm. Without building one.
Institutional-grade crypto signals, calibrated and risk-managed, across your whole universe. The edge of an in-house quant desk, without the pipeline, the models, or the team to run them.
A seven-figure quant desk. Or a contract.
Real signals in-house mean a data pipeline, ML models, backtesting, calibration, and a team to keep it all running. Two paths from where your firm sits today.
Building gives you a seven-figure bill and an eighteen-month wait, with no guarantee it works. Pearlixa gives you the working desk.
Signals you can put client capital behind.
Your LPs will judge the fund by these calls. That is a responsibility we engineered for, not a number we made up.
You don't have to take our word for it. The whole approach is explained in plain terms, the data, the model, and how it is validated, so you can see how the signals are made before you trust them.
See how it worksCalibrated confidence
0.87 behaves like 87%. Size and gate on the number, not a vanity score.
Walk-forward validated
Tested only on data it never saw, rolling forward the way it runs live.
No repainting
Timestamped at delivery. What your clients saw is what the record shows.
Independent by design
An uncorrelated input that diversifies the edges you run, rather than echoing them.
An input you add. Not a system you adopt.
Pearlixa is one independent, calibrated quant signal you weight alongside your own. It builds on the strategy you already run, and fits whatever that strategy is.
Confirmation overlay
Gate your own book so positions only open when Pearlixa agrees and its confidence clears your bar.
Confidence-weighted sizing
Let the calibrated confidence set position size, so a 0.87 setup carries more than a 0.62 one.
Portfolio tilt
Rank your universe by confidence each cycle and tilt allocations toward the highest-conviction names.
Diversifying alpha
An independent, low-correlation signal to diversify the edges your desk already runs.
Your whole book, one request.
A simple API, built for enterprise scale. A few lines and your whole universe of calibrated signals is in your stack, streamed over WebSocket. You wire it into your own systems, not ours.
1from pearlixa import Pearlixa2 3px = Pearlixa(api_key=PEARLIXA_KEY)4 5# one call — your whole book, calibrated6signals = px.batch(universe, horizon="mid")Everything an institution needs, around the API.
No tier caps. Your call budget, set with you.
The fields and coverage shaped to your case.
Real-time streaming, enterprise-only.
Ship the signals as your own to clients.
On the enterprise contract.
A dedicated contact, not a ticket queue.
We move at your speed. Not the other way around.
The pace your desk runs at is our standard, not the exception. A dedicated engineer is with you from the first call, so the work moves as fast as you do, never a vendor queue holding things up.