Led by a team of industry veterans, Context Analytics combines deep market expertise with advanced data science to deliver real-time, context-rich insights for modern decision-makers.
Meet our Team
Executive Leadership
CEO & Founder
Joseph Gits
Founded as SMA, Context Analytics began with the belief that capital markets professionals needed a way to quantify the impact of social media on equities, sectors, and industries.
Experience
Joe is a pioneer in quantitative trading systems, previously co-founding Quantitative Analytics (QA Direct), a leading database platform for quants and traders, before launching Context Analytics.
Over 30 years of financial data and analytics experience
MB Finance from Depaul University, CFA Charter Holder
Experience in ML, NLP & AI in finance space
Umair joined from Thomson Reuters and brings deep experience in building financial applications and large-scale server systems. He leads development of Context Analytics’ core IP
20+ years in software development
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CTO
Umair Rafiq
Kim oversees finance and shareholder accountability at CA, drawing on experience in credit and derivatives from roles at JP Morgan, Bank of Montreal, and others. She holds a B.S. from Indiana University and an MBA from the University of Chicago.
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CFO
Kim Herndon Gits
Zishan collaborates with CA’s product and research teams to deliver data science solutions and new products. He holds an M.S. in Financial Engineering from the University of Illinois.
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Head Data Scientist
Zishan Cai
Our Mission
Our primary focus is transforming traditional and alternative data sources, into actionable insights. Through our solutions, we empower businesses to optimize returns, manage risk, and unlock a deeper understanding of the market.
How Do We Do It?
Context Analytics delivers its solutions through low-latency RESTful JSON APIs, providing security-level data across all asset classes. Our metrics are designed for seamless integration with quantitative models, enabling real-time and baseline access to actionable insights.
Powered By Precision
Sentiment NLP
Context Analytics built its own NLP platform to decode financial language. Our sentiment lexicons span asset classes from ESG to Fixed Income.
Parsing Engine
Context Analytics parses any document into structured, machine-readable JSON. Our output mirrors original hierarchy for human readability and alpha generation.
Source Rating
Source credibility matters as much as the message itself. Our 12-factor algorithm filters bots, spam, and bad actors for clean sentiment data.
Complex Topic Model Engine
Context Analytics built its own NLP platform to decode financial language. Our sentiment lexicons span asset classes from ESG to Fixed Income.
Latest Press Release
AI Developments for the Financial Services Industry
At Context Analytics we are seeing a rise in the deployment of in-house LLMs using Retrieval Augmented Generation (RAG) on cleaned and parsed data. The path to Agentic AI is linking in-house LLMs to algorithms triggering alerts, auto populate reports (analyst reports, credit reports, risk reports, etc.) and even execute some tasks (filing standardized reports, algorithmic trades based on defined triggers).
