Every plan includes paper-trading mode, so you can validate the signals before going live. A hard capital cap protects every account by default.
For individual retail traders. Full paper-trading included.
For RIAs, active traders & family offices.
For hedge funds, prop desks & VC-backed deployments.
| Feature | Personal $49/mo |
Professional $99/mo |
Fund / Enterprise |
|---|---|---|---|
| Symbols | 10 fixed | 50 custom | Unlimited |
| Paper / Demo Mode | Yes | Yes | Yes |
| Live Execution | Alpaca | Alpaca + Tiger | Any broker (API) |
| Model Ensemble | Heuristic + XGBoost | Full (+ DQN/PPO + LLM) | Full + custom models |
| Regime Overlay | Basic | Full (4-factor) | Full + tunable weights |
| Options Analytics (POP, CVaR) | Yes | Yes | Yes + custom strikes |
| Walk-Forward OOS Report | Monthly | On demand | On demand + audit log |
| Capital Cap | $1k / $5k max | $50k configurable | Unlimited |
| Kill-Switch | — | Phone | Webhook + API |
| Alpaca OPRA History | 90-day lookback | Full history | Full + tick data |
| Nvidia GPU Training | Shared | Dedicated slot | On-prem or cloud |
| Support | Priority + call | SLA 4hr + account manager | |
| Source-Code Access | — | — | Escrow available |
Beyond QuantAI, InfuseAI delivers end-to-end ML/DL for enterprise, research & government. Nvidia-certified. PhD-led. Production-proven.
End-to-end Nvidia-stack deployment: NeMo, Nemotron-3.5 ASR, Triton Inference Server, Dynamo, the KAI scheduler with the Grove operator, and CUDA multi-GPU training. We've shipped production inference serving large concurrent user bases — certified by Nvidia, the only certified DL instructor in NZ.
Custom LLM pipelines on open-weight models (GPT-OSS, Gemma, Llama, Qwen) and frontier cloud LLMs, with RAG for secure on-premise document intelligence — context windows to 128K+, plus agentic workflows for research, compliance and knowledge management. Proven at senior-leadership scale.
Vision Transformers and CNNs (ViT, EfficientNet-V2) for medical-imaging outcome prediction, industrial defect detection, and 3D LiDAR driver-assistance (ADAS hazard detection). We improved accuracy from 40% to 95% where human experts failed; +23.1% on industrial anomaly detection.
Full ML engineering lifecycle: ETL/ELT pipelines, Nvidia KAI (Grove) GPU schedulers, hyperparameter optimisation (Optuna + novel entropy methods), experiment tracking, Docker/Singularity, AWS/GCP. We've cut training time by up to 45%.
Temporal modelling with Transformers, RNN/LSTM and XGBoost for financial forecasting, industrial PID control and anomaly detection — the same methodology underpinning QuantAI.
Engagements scoped individually — from 4-week POCs to 12-month embedded delivery.
Discuss a ProjectWe're raised a seed round to accelerate QuantAI commercialisation, we need a Series A/B round to scale. For VCs, angels and trading firms interested in co-investment, white-label licensing, or an acquisition conversation — we'll share the full technical deck, walk-forward audit trail, paper-trading P&L history, and a code-architecture review.