A generative AI copilot is transforming portfolio intelligence and investment analysis at Corbin Capital, where portfolio managers previously struggled to access timely insights from hundreds of complex financial documents. With over 43 major holdings, some valued over $100 million, Corbin’s promise of bespoke portfolios for high-end clients was slowed down by manual research, siloed information, and inaccessible historical data.

To deliver on its premium service promise, Corbin needed a smarter, faster way for its team to analyze assets, compare portfolios, and derive insights, without months of manual review.

The problem: insight bottlenecks for high-value portfolio intelligence

Corbin Capital’s edge lies in tailoring investment strategies across alternative asset classes. But this required portfolio managers to deeply understand each asset’s performance, historical behavior, and structural details, buried inside a mountain of PDFs, spreadsheets, and reports.

Manual deep dives into documents often took weeks or months. Senior portfolio leaders lacked a unified view, struggled to compare assets in real time, and faced delays in offering timely advice to clients.  

With each client expecting highly personalized portfolio strategies, Corbin needed to streamline how their teams extracted knowledge and collaborated across asset types.

The solution: a generative AI copilot for real-time portfolio intelligence

To solve this, GoML partnered with Corbin Capital to build a secure, scalable Gen AI copilot powered by GPT-4 Turbo. This AI copilot ingested all structured and unstructured data, including documents, spreadsheets, scanned reports, and even audio transcripts, across portfolios.

Using a Retrieval-Augmented Generation (RAG) framework, the solution enables portfolio managers to query historical data, extract asset-specific details, run mathematical functions, and compare holdings, all using natural language.

The copilot was built with enterprise-grade security and auditability in mind, integrating with Corbin’s existing SharePoint repositories, Azure Cosmos DB, and identity systems. Designed to scale with their growing investment base, it now serves as the single source of truth across their portfolio team.

Always-on portfolio intelligence with Gen AI

• Conversational interface for finance teams

GPT-4 Turbo enables intuitive queries like “Compare 3-year returns of Holding A vs Holding B” or “List all assets with over 20% volatility last year.”

• Portfolio comparison & insights

The copilot surfaces differences in asset structures, risk profiles, and historical performance in seconds, enabling smarter recommendations.

• Mathematical modeling & reporting

Users can run calculations like Sharpe ratios or CAGR directly in the chat interface, with outputs embedded into PDF-ready reports.

• Built for compliance and control

Authentication layers, access logging, and audit trails ensure data privacy. The system meets financial compliance standards and restricts visibility by role.

Intelligent, secure, and scalable architecture for AI enabled portfolio intelligence

Data Processing Layer

• Portfolio documents ingested from SharePoint and GitHub repositories

• Preprocessing of PDFs, scanned documents, tables, and multimedia

• Indexed and stored in Azure Cosmos DB with secure access

Intel Layer

• RAG pipeline built on GPT-4 Turbo

• Embedded document vector search via Azure OpenAI and Cognitive Search

• Role-based access controls and usage tracking

Consumption Layer

• React.js frontend with secure SSL on Linux VM

• Real-time queries, comparisons, and custom report generation

• Usage analytics and feedback loop for continuous improvement

The impact: faster insights for smarter portfolio intelligence

GoML’s generative AI copilot has revolutionized how Corbin Capital engages with portfolio data. Portfolio leaders now access insights in minutes, not months, and use these to build more personalized and timely strategies for clients.

“GoML helped us unlock the intelligence within our documents. Now, our portfolio teams spend less time searching and more time advising,” said a senior executive at Corbin Capital.

What can other portfolio management firms learn?

Key pitfalls to avoid

• Relying only on spreadsheets for high-value portfolio insights

• Ignoring data governance and access control in AI solutions

• Building tools without domain-specific NLP capabilities

Advice for transformation leaders

• Start with high-impact use cases like portfolio comparisons and reporting

• Ensure your AI partner understands both LLMs and financial compliance

• Focus on scalability and usability from Day 1

Want to build a Gen AI copilot for your asset management workflows?

Let GoML help you modernize how you extract intelligence from financial documents with secure, scalable AI solutions built for alternative asset firms.