AI for investment decisions

Tailored AI solutions for professional investors

How it works

From market data to monitored investment signals.

01

Ingest

Market, macro, alternative, and proprietary data are cleaned, normalized, and prepared for repeatable research.

02

Engineer

Predictive features are built across asset classes, horizons, and market regimes.

03

Train

Models are trained against defined targets and validation windows, with diagnostics designed for real use.

04

Deliver

Signals, forecasts, rankings, risk filters, reports, dashboards, APIs, or files can support investment workflows.

What your agent does

One AI layer for signals, risk, benchmarking, and pure alpha.

Invest Agent can act as a signal layer, benchmark engine, risk overlay, or dedicated alpha engine depending on the mandate.

Diversify risk

Use AI signals across asset classes to reduce dependency on a single source of return.

Lower drawdowns

Add regime-aware filters, volatility controls, downside alerts, and model-driven risk thresholds.

Buy IA signals

Receive model-generated signals for selected markets, horizons, and delivery formats.

Benchmark strategies

Compare internal strategies against independent AI signal families and diagnostics.

Create pure alpha

Build research workflows that turn data, model selection, and backtesting into alpha candidates.

Dedicated solutions

Develop asset-class-specific products for currency, volatility, equity index, crypto, or cross-asset mandates.

Prediction factory

Built for professional evaluation, not black-box theatre.

Outputs are built for validation and monitoring, with attention to drift, costs, drawdown behavior, and market regimes.

SignalsForecasts, rankings, alerts, and risk filters.
BenchmarksIndependent IA comparison against internal strategies.
MonitoringLive performance review, drift detection, VaR, and drawdown controls.
DeliveryReports, dashboards, APIs, or files for research and investment teams.

Team

Focused quant, data, and engineering expertise.

Invest Agent is backed by two years of R&D across financial markets, machine learning, and production-grade software engineering.

2yDedicated R&D to move from research prototypes to an industrial alpha-production workflow.

Computer engineering

Data science

Financial markets

Build your agent

Commercial inquiries / book a call

Tell us what you are trying to predict, which markets matter, and how you want to use the output.