01 Consulting

Strategy, Infrastructure
& AI Integration

You have the model. We ensure it survives contact with production.

  • Quantitative Strategy Audit — Lookahead and survivorship bias detection, hyperparameter overfit diagnostics, walk-forward robustness testing, live vs. backtest performance attribution, and model lifecycle monitoring in production
  • AI & ML Infrastructure — Scalable data pipelines for LLMs, vector database architecture, prompt leakage prevention, and model lifecycle monitoring in production
  • Systemic Risk & Execution — Latency profiling, risk system design, and execution-aware strategy structuring for TradFi, Crypto, or general algorithmic systems

We operate at the boundary between your research environment and production: ensuring clean data flows in, decisions flow out correctly, and nothing leaks in between. Your signal logic stays in your hands. For funds, prop desks, protocols, and AI-driven data companies building or scaling infrastructure.

Book Discovery Call →
strategy_audit.py
gap research production backtest live pnl

02 Training

Sharpening the
Quant & AI Edge

The gap between a working prototype and a robust production system is where most teams get stuck.

  • Workshops — Intensive half or full-day sessions on systematic trading, backtesting rigour, and ML-driven signals and LLM operationalization; built around real case studies, not toy examples
  • Practitioner Courses — Structured programmes covering factor construction, risk sizing, and execution-aware strategy design; paced for working professionals
  • Custom Programs — Tailored to your team's existing stack, asset class or AI domain, and knowledge baseline

Participants leave with frameworks they can apply the next trading day — and the vocabulary to hold informed conversations with quant developers and risk teams. Built on 10+ years of live trading, AI research and university-level teaching experience.

View Programs →
orchestrator.yaml
ALGO TRADING quant infra data exec ml

03 Data Pipeline & AI Audit

The Foundation
of Intelligence

Your model looks great in isolation. Your live performance doesn't match. Why?

  • Data Quality & Integrity — Gaps, survivorship bias, look-ahead contamination, stale feeds, and schema drift
  • Model & LLM Operations (MLOps) — Data leakage in training sets, prompt injection risks, vector similarity decay, and reproducibility of AI outputs
  • Execution & Latency Analysis — Fill rates, slippage patterns, market impact, funding cost drag, and where milliseconds accumulate to decay alpha
  • Pipeline Architecture — Identifying bottlenecks in ETL processes, ensuring deterministic data flows, and optimizing storage/retrieval for AI workloads

We deliver a written diagnostic report with ranked findings and concrete remediation steps. What you do with your signals or models afterward is entirely your business. We find the leaks. You keep the returns.

Request Audit →
zk_pipeline_architecture.sh
market data ingest cleaner ⚠ gaps survivorship bias detected strategy engine signals exec → latency: 2ms 87ms 14ms 1ms

Built on Production Experience

The gap between research and production is where most projects fail. That's where we work.

Aqfinea is a quantitative and AI consultancy. We come from academia, hedge funds, and crypto vaults and tech-scale data engineering. We've built strategies that trade live, systems that power AI applications. We've taught the theory. We know where backtests break — and why live performance rarely matches the curve.

Our work covers systematic strategy design, quant development, AI/ML infrastructure, and execution optimization. We do not manage your capital, and we do not need to understand your alpha to do our job well.

10+
Years of live trading & AI/data engineering experience
3
Service tracks: consulting, training, pipeline/AI audit
0
Access required to your proprietary strategy logic or model weights
∞
Gap between backtest performance and live PnL