qMachina

AI-agent-native strategy testing

Hedge-fund-grade futures backtesting. From a sentence.

qMachina brings hedge-fund-grade accurate fill simulation and AI-agent-native strategy backtesting to retail futures traders, powered by patent-pending technology. Describe your thesis in natural language, turn it into a testable strategy, and see how it behaves in market context.

  • Retail futures traders
  • AI-agent ready
  • Patent-pending fill-sim technology
Request Access How It Works
STRATEGY RUN FUTURES · L3 REPLAY
YOUR IDEA

“Fade an opening extension when buying pressure exhausts and the queue turns.”

AI-BUILT STRATEGY Opening Exhaustion Fade
  • Detect opening extension
  • Confirm queue imbalance reversal
  • Define entry, risk, and exit rules
FILL MODEL: FIFO + LATENCY VALIDATION RUN READY

From idea to an answer

How It Works

qMachina puts a hedge-fund-grade research loop in the hands of retail futures traders. Bring your own idea, or let an AI agent use qMachina resources to create, test, inspect, and refine it.

  1. Describe the setup

    Start with the way traders actually think: a market condition, an entry idea, a risk rule, or a pattern you want to challenge.

  2. Build the strategy with AI

    An AI agent consumes qMachina resources and turns the idea into explicit, editable rules. You keep the strategy logic in an explicit specification.

  3. Replay the actual market context

    Test against retained futures and futures-options market data with strict no-lookahead replay, so the strategy sees the market one moment at a time.

  4. Validate the fill simulation

    qMachina's patent-pending technology tests fills against FIFO queue position, displayed liquidity, and explicit latency assumptions—giving every backtest a stronger, more accurate foundation.

  5. Inspect, adjust, run again

    Read the strategy chart, trade list, fill diagnostics, and equity curve. Then ask your agent to revise the rules and run the next test.

Fill fidelity is the product

Patent-Pending

qMachina is developing patent-pending technology for validating accurate fill simulation and strategy testing. It is designed to bring order-book mechanics—queue position, displayed liquidity, latency, and strict replay timing—into a research experience retail futures traders can use directly.

qMachina lets you examine the rules, the market context, and the simulated fill behind every trade, then iterate with your AI agent from a concrete record.

Every strategy result, in context

Results

An AI-built strategy becomes a durable research asset. qMachina puts the rules, chart, trades, and fill behavior in one research loop.

STRATEGY REPORT

Opening Exhaustion Fade · Futures

REPLAY COMPLETE

A strategy specification

Turn natural-language intent into clear entry, exit, sizing, and risk rules an AI agent—and you—can edit.

A chart you can challenge

Move from the equity curve to the exact trades and market moments that created it. Good questions become the next version of the strategy.

Fill diagnostics

Inspect queue position, latency assumptions, and order-book context behind each simulated fill.

Institutional-grade research. Built for retail futures traders.

Futures first

A strategy-testing workspace designed around the pace, structure, and fill sensitivity of futures and futures-options trading.

Market context

Full-depth replay and strict timing rules give the strategy and its AI agent the context to test ideas one market event at a time.

A better feedback loop

Move from idea to rules, chart to fill trace, and first version to next test without losing the thread of your original thesis.

Get started

Request Access

Tell us what you want to test. We are looking for futures traders and teams who want to turn their best ideas into stronger strategy research.

Beta intake is opening shortly. The request channel will activate when the program opens.

FAQ

What instruments does qMachina cover?

qMachina is built for futures and futures-options strategy research with the market context required to examine strategy fills.

How do AI agents work with qMachina?

Give an agent a market hypothesis in plain language. It can use qMachina resources to create explicit strategy rules, run the replay, and refine the next version with the results in view.

What makes the fill simulation different?

The test can inspect FIFO queue position, displayed liquidity, and latency in the replayed order book. The patent-pending validation approach is designed to make those assumptions visible and testable.

Can I inspect the strategy after AI creates it?

Yes. The goal is an editable strategy specification. Inspect the rules, chart, trades, and fill diagnostics, then change the idea and rerun.

What does “patent-pending” mean?

qMachina's patent-pending technology is focused on accurate fill simulation and strategy testing for futures traders.

What do I get back from a strategy run?

An editable strategy specification, a replay chart, trade list, equity curve, and fill diagnostics you can inspect with your agent or team.

How do I get access?

Through the Request Access section on this page. If intake is closed when you visit, the form will say so plainly.