QIX·LABSEarly access

AI agents for finance

An autonomous quant-research team — validated before it touches capital.

QIX Labs builds Flow: an AI agent workforce that automates quantitative research and adversarially validates every result before it reaches capital — the research power of a large quant desk, with a lean team.

Fig.1 — a candidate signal, headed for the gauntlet
vol spikereversalσt →

Incorporated in Singapore

The problem

Alpha doesn’t scale — it’s bottlenecked on humans

The human bottleneck

A skilled researcher validates roughly one real idea a week — literature, implementation, backtest, leak-checks, cost and capacity, sign-off. Days per idea, mostly plumbing. Meanwhile every alpha decays by the day.

The AI trap

A frontier model proposes a hundred strategies an hour. That is the problem, not the solution: more search means more spurious patterns. “AI for alpha” is an overfitting machine — unless it is chained to an equally powerful refuter.

A false negative costs a day. A false positive costs a blown-up book.

Flow · the product

Quant research as a compounding production line

Flow turns quant research into an automated, compounding production line — and gives the firm one view across every signal it has ever tested. Days of human plumbing collapse into hours of machine search, every step logged and reproducible.

AI proposes, human disposes. Every live decision stays behind a human sign-off and hard caps.

The agent fleet

Six agents, one research team

Each agent owns one job in the cycle — tireless, parallel, and consulting a shared memory before every run.

Scout

Surveys the literature and data; proposes 20+ strategy families, each with an economic prior.

Builder

Turns each hypothesis into backtest-ready strategy code on one canonical engine.

Validator

Runs the full gauntlet: lookahead, overfitting, multiple-testing, hidden beta.

Red-Team

Adversarially attacks every survivor — trying to kill it before capital does.

Synthesizer

Blends survivors; checks correlation, crowding, and whether each one truly adds value.

Librarian

Logs every result — win or dead-end — to a permanent, searchable memory.

The research cycle

An automated production line for alpha

  1. 01

    Hypothesize

    From data and prior research, propose testable investment ideas.

  2. 02

    Design

    Structure each idea into concrete, falsifiable research questions.

  3. 03

    Explore

    Build and backtest many candidates on real market data, in parallel.

  4. 04

    Validate

    Run the gauntlet; kill what doesn’t survive; keep the evidence.

  5. 05

    Learn

    Wins and dead-ends feed memory — the next cycle starts smarter.

Days of human plumbing collapse into hours of machine search — every step logged, reproducible, and fed back into the loop.

Validation

Most verdicts are an honest “no”

Every candidate runs an adversarial gauntlet built from real failure modes — lookahead, overfitting, multiple-testing, hidden beta, capacity. The output is a clear PASS / REJECT with full evidence, logged to memory.

The product is the refutation, not the generator — and that is what earns the trust to deploy.

momentum_kr_largecapKR large-cap · 2018–2024
CheckResultDecision
Sharpe ≥ 0.800.84PASS
Max drawdown < 35%−29%PASS
No lookaheadcleanPASS
Cost survives 20 bps0.71REJECT
Out-of-samplequeuedPENDING

Institutional memory

A big picture of every signal

Every experiment is logged
Wins and dead-ends alike become structured, permanent records — nothing is re-walked twice.
A searchable organizational brain
Query what has been tried, what worked, and what failed — instantly, before the next run.
A compounding, defensible edge
The map grows with every cycle; duplicated research disappears and the firm’s knowledge accrues.
Signal map154 experiments
validated dead-end untested

Validated, dead-end, untested — one map.

Built for

Small and emerging investment firms

Boutique managers, prop desks, family offices, and new funds that can’t justify a large quant team — given the research power of one.

Fewer quants, more output

The research throughput of a large quant desk, with a lean team.

Speed to verdict

Validated ideas in days, not weeks — capture signals before they decay.

Rigor you can audit

Every result independently validated and fully traceable, end to end.

A senior quant costs $300k+ a year. Flow validates a strategy idea for a few dollars of compute — on the order of 100× lower cost per tested idea.

// early access

Put an AI quant team to work.

Flow is rolling out to a first group of small and emerging investment firms. Tell us about your desk and we’ll be in touch.