DATA PIPELINE
Tick-to-signal data pipeline
Raw market data ingested, cleaned, and structured into a factor library feeding live ML signal generation. Sub-millisecond latency, terabyte-scale.
Why most funds stay behind
Generic tools weren't
built for this.
Most funds run on infrastructure designed for general business. That's the gap we close.
Quant pipeline · liveprocessing
Raw market data
Tick feedsAlt dataOptions chain
Factor library
News sentimentCross-asset factorsAlt-data embeddings
ML signal output
Alpha scoreConfidencePosition size
Signal generatedtrade ready
01 — Data infrastructure
Data that breaks at scale
Off-the-shelf pipelines weren't designed for tick data, factor libraries, or alternative datasets. We build ones that are.
02 — Alpha generation
Models without domain depth
Generic ML misses Alpha. Signal extraction requires financial context baked into the feature engineering — not bolted on later.
03 — Operations
Systems that don't talk to each other
Investor ops, deal flow, and team workflows on disconnected tools kill speed. We wire them together.
T+0 sync
Data freshness SL
1M features/hour
Signal throughput
Daily full refresh
Retrain cycle
我们如何介入
为合规、韧性和执行力而设计。
我们聚焦最容易阻断安全扩张的治理、报表和交付问题。
代表性工作
强监督应该长什么样。
以下示例展示的，是执行压力上升时管理层最常要求看到的报表视图、控制材料与治理结构。
QUANT INFRASTRUCTURE
Backtesting framework
Walk-forward strategy validation with drawdown analysis and multi-regime testing across historical data.
- Walk-forward validation with drawdown analysis
- Multi-regime and out-of-sample testing
FUND OPERATIONS
CRM & fund ops build
Deal flow, investor relations, HR onboarding and reporting — wired together for a lean fund team.
- Deal flow and investor relations CRM
- HR onboarding, reporting, and workflow automation
以下为代表性项目形态与示意输出，不含虚构客户、标识或绩效声明。