We build bespoke data infrastructure, intelligence workflows and process automation for specialist advisory firms that need institutional-grade analytical capability — without building a full internal engineering team.
Quantitative data engineering from Nomura, Insight Investment and Loomis Sayles — combined with 25 years of institutional FX and macro investing across GAM Investments, Capula and Dragten Capital Solutions.
The common challenge is not the absence of technology. It is that the underlying data processes are too fragmented and manual to support systematic analytical work.
Matter chronologies from source documents. Regulatory change monitoring. Evidence extraction and pack structuring. Disclosure workflows. Corporate filings intelligence for clients and transactions.
Buyer universe generation. Sector monitoring. Target screening from databases, filings and public records. CRM enrichment. Market maps. Precedent transaction research. Diligence pack automation.
Repeatable research workflows that eliminate manual data gathering. Internal knowledge bases with source attribution. Client dashboard delivery. Market intelligence monitoring and report generation.
Most advisory firms' analytical capability is constrained not by the absence of tools, but by the absence of structured data processes to feed them.
Partners, directors and senior analysts spend hours on data gathering that should be automated. Every hour of senior attention spent on manual research is an hour not spent on client work, deal execution or strategic decisions.
Critical information sits inside PDFs, regulatory filings, email threads, CRM exports and website pages. Without a structured acquisition layer, this information cannot be compared, tracked or used systematically.
Regulatory change, corporate announcements and market intelligence that should be caught in real time are discovered days late — because there is no systematic monitoring infrastructure watching the right sources.
AI pilots fall short when the underlying data is too fragmented, unstructured and inconsistently sourced. The technology is rarely the limiting factor — the data architecture is.
Every engagement starts with understanding the specific workflow and ends with a system the team can use without further engineering involvement.
Understand the workflow, the data sources, the current manual steps and what the output needs to look like to be useful to the senior team.
Assess what data is available, where it lives, how to acquire it reliably and what structure makes it most useful for downstream analytical work.
Build a working version with real data from your actual sources so you can see the output before committing to a full production deployment.
Deploy a reliable, maintainable system with scheduled runs, monitoring, source attribution and output in the format the team actually uses.
Our team has delivered data infrastructure across front-office environments at Nomura, Insight Investment, BNY Mellon and Loomis Sayles. The systems below are in active production — built to the same standard applied to every client engagement.
Real-time port monitoring, maritime AIS tracking, container flow analysis and supply chain disruption signals from satellite imagery and shipping data.
Satellite-based asset monitoring, mineral signature analysis, site activity tracking and disturbance detection for global mining operations.
Entity tracking, facility monitoring, movement intelligence and open-source intelligence workflows for sensitive analytical applications.
Automated macroeconomic data feed covering 500+ indicators across 11 major FX economies — GDP, inflation, interest rates, trade balances and monetary policy — updated on a recurring schedule with a clean 50,000+ row audit trail.
GeoAnalytic brings together quantitative data engineering experience from front-office asset management and multi-decade currency markets and macro investing depth — combining systems rigour with institutional finance judgment.
Former quantitative analyst and data systems architect with front-office finance and production data-engineering experience at Nomura, Insight Investment / BNY Mellon and Loomis Sayles — environments where the cost of a broken data workflow is measured in real money.
Derivatives pricing systems and C++ analytics libraries for quantitative teams supporting hedge fund and prop-shop clients.
Currency quant team. Real-time data pipeline systems for portfolios with approximately $50B AUM exposure.
ESG data pipeline architecture for a Boston fixed-income asset manager. $2B+ compliance infrastructure built from scratch.
Senior currency and macro markets specialist with more than 25 years of institutional finance experience across GAM Investments, Element Capital Partners, Capula Investment Management and Insight Investment. Through Dragten Capital Solutions, Mark advises international businesses on currency exposure, hedging strategy and FX risk governance.
Thirteen years managing interest rate and FX portfolios across long market cycles, covering derivatives, options and discretionary macro strategies.
Senior portfolio management role in institutional macro investing and currency markets, following roles at Capula Investment Management and Element Capital Partners.
Advisory practice helping international businesses manage currency exposure, hedging frameworks and treasury risk in volatile global markets.
Describe the research, monitoring or data process that consumes the most senior time. We will assess whether it can be structured, automated or systematised — and what a production version would look like.
