AI Large Models
Proprietary and integrated large models for market analysis, signal research and automated decisions.
We treat large models as production systems, not demos. A model has to run continuously against live market data, be evaluated, and be rolled back — so we built evaluation, monitoring and version management around it.
Sentiment & news analysis
Structured extraction and sentiment scoring over news, filings and social signals, emitted as time-series features downstream strategies can consume.
Multi-factor signal research
Model output is fused with conventional price/volume and fundamental factors, then orthogonalized and weighted to reduce dependence on any single signal source.
Automated decisions & execution
Signals pass through the risk layer before entering the execution queue. Every decision is traceable back to the inputs that triggered it.
Evaluation & regression
Models run historical replay before release, and expected-versus-actual performance is compared continuously after. Deviation past threshold alerts and supports rollback.
Observable before automated
No model gets decision authority until it has run a full observation cycle in read-only mode.
Traceable inputs
Every signal traces back to specific input data and a model version. That's the precondition for being auditable.
- Inference serving
- Vector retrieval
- Feature store
- Eval pipeline
Want to go deeper?
Whether it's technical integration or an institutional partnership — talk to us directly.