Most bots ask you to trust them. QuantAI asks the data first.
An AI trading edge lab that measures cost, latency, risk and signal quality — before execution.
QuantAI asks a different question first: is there still edge after cost, latency, slippage and risk? In measured examples, round-trip cost hurdles ranged from viable to structurally untradable — depending on venue, fee model and trade size.
Every strategy must beat its measured cost hurdle — with pre-registered hypotheses and honest sample sizes — before it earns any execution.
Fees, spread, slippage and latency — measured per venue, per hour, per trade size.
Replay → shadow → paper → guarded live. Strategies earn promotion.
AI proposes. Policy decides. An isolated executor acts.
Intent, risk checks, approval, fill, reconciliation — every decision leaves a trail.
NO_TRADE is a feature. Below the hurdle, the system refuses — that's not a failure, that's the product working. Missing data never becomes a trade: unknown fails closed.
Ever. Every action becomes an intent that must survive the full chain — and everything is audited.
A model proposes. Proposals are cheap — that's all they are.
The proposal becomes a structured, inspectable intent. Never an order.
Position, exposure and drawdown limits. Fails closed.
Execution posture, venue rules, cost hurdles. Fails closed.
Human sign-off — automation itself is a gated, constitutional decision.
Who approved what, when, under which limits. Receipts survive.
Multi-venue fee, minimum-order and API studies with sources — including the venues where micro trading is structurally untradable after costs.
Spread, depth, simulated slippage and latency — sampled continuously from public order books, summarized by hour, judged against pre-registered thresholds.
Decides for real, executes in simulation with measured costs and latency realism. Ships with a control strategy that never trades — if the control ever "profits", the system is broken. That test ships with the product.
Expected edge below 1.5× measured cost means no trade — by law, not by mood.
Paper/live separation, execution posture and governance state — always visible, never buried.
Signals seen, intents created, and — proudly — how many were blocked, cancelled or rejected.
Display-only market regime context. A label is never an order.
The full chain of every decision, from signal to audit, on one screen.
Who approved what, when, under which limits. Receipts, not vibes.
Each level is unlocked by proof, policy and human sign-off — never by excitement.
No — and be suspicious of anyone who does. QuantAI guarantees the truth about your strategy: if there is no edge after costs, you find out in simulation, before it costs you money.
Never. There is no direct AI-to-broker path by architecture. AI proposes an intent; risk gates and policy decide; execution happens in an isolated, audited layer.
No. Live is the last step of a gated ladder — shadow, then paper, then guarded live — each unlocked by evidence, policy and legal review.
The system measured the expected edge, subtracted real costs and risk, and found the result below the hurdle. Refusing that trade is the product working.
One number: gross signal edge minus fees, spread, slippage, latency and risk. It decides — TRADEABLE, WATCH, NO_TRADE or UNKNOWN. Unknown always fails closed.
The engine decides for real but executes in simulation against live public market data, with measured costs and latency.
Because costs are where strategies actually die.
No. QuantAI is research and execution-governance software. Nothing here is investment advice.
We publish it. A killed thesis is a success of the lab.
Private beta is design-partner based. Use the Request Private Access button.
For traders who would rather measure first than believe first.
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