Quant infrastructure & trading automation that just works.

We design and run broker/exchange connectors, risk middleware, and execution algos so your strategies go from research → backtest → live with parity, guardrails, and observability. Results in weeks, not months.

We build software for research & operations. Nothing here is investment advice.

Production-grade stack

Trading-grade stack, proven & popular

Python
PostgreSQL
Docker
AWS
C++
.NET / C#
Apache Kafka
Redis
kdb+ (KX)

Quant & trading tech, end-to-end.

Strategy research & backtesting

From idea to robust edges with walk-forward & Monte Carlo

AI/ML alpha discovery

Feature engineering, model training, cross-validation

Exchange & broker connectivity

FIX / REST / WebSocket integrations for major venues

Low-latency execution

Event-driven engines, smart routing, slippage controls

Data pipelines

Tick/OHLCV ingestion, cleaning, corporate actions, storage

Monitoring & alerts

Real-time PnL, risk, anomalies; alerts to chat/email

Secure cloud deployment

Docker/K8s on AWS/Azure with CI/CD and IaC

Support & consulting

Hands-on help from quant engineers for your use case

Research → Live

What a production trading system actually looks like

Every stage has failure modes that only appear in live trading. Explore each one to see what it involves, and what breaks when it's done wrong.

Data

Ingestion & storage

Clean, aligned market data is the foundation of every reliable system. Bad data produces bad signals, regardless of how good your model is.

  • Tick and OHLCV ingestion from exchanges, brokers, and vendors
  • Gap detection, corporate action adjustments, timezone normalization
  • TimescaleDB for time-series, PostgreSQL for metadata and positions
  • Full replay capability: backtest under the exact historical conditions that existed

Stack

TimescaleDBPostgreSQLKafkaRedisPython

Common failure

Missed gaps or misaligned timestamps cause strategy logic to fire on phantom signals.

Products & Building Blocks

Research→Test→Deploy Framework

New

Private Python scaffold to move ideas from notebooks to walk-forward tests to live with config parity and risk rails.

Python
Backtesting
CI/CD
Docker

Live Strategies on Popular Frameworks

Strategy implementations and adapters for Nautilus Trader, NinjaTrader, and MT5: data, execution, and risk wired up.

Nautilus
NinjaTrader
MT5
REST/WebSocket

Crypto Bots & Alerts

On-chain/cex signal bots with threshold logic, schedule windows, and alerts to Telegram/Slack/Email.

Crypto
Webhooks
Alerts

Strategy Performance Analyzer

Aggregate runs, P&L breakdowns, factor exposures, drawdowns, turnover, and costs. Exportable reports.

Analytics
P&L
Drawdown
TCA-lite

Scenario / Pattern Analyzer

Search repeating setups on an asset, slice by variables, and estimate conditional edge & probabilities.

Pattern Mining
Stats
Resampling

Paper→Live Switchboard

Single config to toggle paper/live per venue with safety checks and runbooks.

Routing
Safety
Config

Risk Limits & Kill-Switch Service

Per-strategy/day limits, circuit breakers, position caps, and emergency kill across venues.

Risk
Limits
Kill-switch

Data Quality Monitor

Detect gaps/outliers, corp-actions mismatches, and stale feeds; alert & auto-quarantine bad data.

Data QA
OHLCV/Tick
Alerts

Execution Cost / Slippage Reporter

Venue-aware slippage & fees report with benchmarks vs. mid/arrival; CSV & dashboard.

TCA
Slippage
Fees
shipping production software
3+
years
design, build, deploy, maintain
in crypto markets
3+
years
systematic trading, data & execution
long-term clients
6+
multi-project, referenceable
products shipped
10+
apps, services & trading systems

Questions and Answers

Contact Us

Get in touch with our team. We'll respond to your message as soon as possible.

Stop leaking edge. Fix execution, data, risk.