How a Multi-Class Asset Management Fund Uses AI Agents to Streamline Research, Compliance, and Reporting

How a Multi-Class Asset Management Fund Uses AI Agents to Streamline Research, Compliance, and Reporting

A multi-class asset management fund used StackAI to automate research, compliance, and investor reporting—cutting reconciliation time by 80%.

Client

Multi-Strategy Asset Management

Challenge

Manual, error-prone reconciliation and fragmented research workflows slowed decision-making and compliance across complex fund entities.

Solution

StackAI unified data extraction, retrieval, and document generation into governed AI agents that automated analysis, reporting, and multi-entity compliance.

Overview

A leading multi-class asset management fund, managing billions in capital across multiple vehicles, uses StackAI to modernize internal research and reporting workflows.

The fund’s data science and operations teams were already highly technical, running custom tools connected via internal APIs, but the complexity of multi-class assets, historical fund structures, and evolving compliance standards created significant operational drag. Across accounting, compliance, and research, the fund’s analysts and data scientists faced several recurring challenges:

Fragmented data across internal APIs, Excel workbooks, and decades of fund documentation
Manual report generation that slowed decision-making
Increasing compliance overhead tied to capital account reconciliations
A lack of standardized knowledge retrieval for portfolio and investor communications

The team needed a way to automate information retrieval, validation, and reporting, without sacrificing control, auditability, or data security.

StackAI empowered the team to orchestrate agentic workflows that connect directly to internal systems, automate compliance checks, and synthesize years of institutional knowledge into actionable insights. Since deployment, the fund has reported:

80% reduction in manual compliance and reconciliation hours
10× faster data retrieval and report generation
Seamless integration between technical and non-technical teams using governed, audit-ready workflows

Streamlining Fund Reporting

The Problem: Slow and Fragmented Performance Reporting

Performance and exposure data lived across several internal systems. Analysts often needed to query multiple APIs to build custom reports summarizing fund performance by company, manager, or time period.

Each query required manual parameter selection and data validation, which limited throughput and made ad-hoc research difficult.

The Solution: Custom API Orchestration for Research

Using StackAI’s API integration framework, the team connected their internal data warehouse to a series of custom endpoints. Agents could now interpret natural-language prompts (e.g. “List total market value per company for Q3 2025”) and automatically use LLMs to:

1. Identify the correct internal APIs to call (e.g. performance, holdings, exposure).

2. Retrieve the right parameters (dates, fields, filters).

3. Generate a consolidated table with source-linked audit logs.

This API-driven orchestration turned hours of manual querying into seconds, allowing data scientists to focus on modeling and interpretation instead of plumbing.

Automating Capital Account Verification

The Problem: Compliance Burden in Capital Account Reconciliation

For each quarterly close, the fund’s accounting and compliance teams needed to reconcile thousands of capital account statements across dozens of legal entities and fund structures—each with its own allocation methodology, reporting period, and data schema.

Capital accounts record each investor’s ownership position over time, showing how contributions, distributions, and net asset value (NAV) changes roll up to the fund’s total equity. In a multi-strategy structure, these accounts become highly fragmented: one investor might appear across multiple feeder funds, each tied to distinct legal entities or classes.

Historically, reconciliation meant manually verifying PDFs, Excel models, and ledger exports line by line to confirm that capital movements (calls, redemptions, allocations) aligned across all entities.

This process consumed hundreds of hours per quarter, invited human error, and made auditing slow and reactive. When discrepancies appeared, there was no single, traceable view linking extracted values to their original documents.

The Solution: Automated Capital Account Workflow

Using StackAI, the fund built an agentic workflow that automates capital account verification across all entities while preserving full governance and auditability.

The workflow runs through three main stages:

Data Extraction: The agent parses uploaded capital account statements (PDF or Excel) using OCR and advanced parsing models, extracting key values such as beginning balance, contributions, distributions, gains/losses, and ending balance.
Entity Matching: A second node cross-references these records against a Legal Entities Reference table, ensuring every record maps to the correct entity, share class, and internal ledger ID.
Validation and Reporting: The agent automatically compares extracted values against the general ledger, flags discrepancies, and generates a structured reconciliation summary with direct links to the source statements.

The outcome?

80% reduction in manual reconciliation time
Elimination of cross-entity mismatches through automated mapping
Defensible, end-to-end audit trail linking every extracted figure back to its original capital account file

Enriching Investor Communications, Efficiently

The Problem: Information Overload in Investor Communications

With multiple strategies and entities, preparing investor newsletters required consolidating performance summaries, compliance notes, and commentary from years of historical documents.

Teams often spent days searching across shared drives and legacy reporting folders.

The Solution: Knowledge Retrieval for Investor Reporting

StackAI’s Retrieval-Augmented Generation (RAG) framework was applied across the fund’s document corpus, spanning investor memos, quarterly letters, and regulatory filings from the past decades.

Now, when preparing a newsletter or internal briefing, an agent can:

• Retrieve the latest fund updates and performance data.

• Surface comparable historical commentary from similar periods.

• Generate draft communications in the fund’s internal style guide.

This means faster turnaround for investor-facing materials and improved consistency across all communications.

Enriching Investor Communications, Efficiently

The Problem: Information Overload in Investor Communications

With multiple strategies and entities, preparing investor newsletters required consolidating performance summaries, compliance notes, and commentary from years of historical documents.

Teams often spent days searching across shared drives and legacy reporting folders.

The Solution: Knowledge Retrieval for Investor Reporting

StackAI’s Retrieval-Augmented Generation (RAG) framework was applied across the fund’s document corpus, spanning investor memos, quarterly letters, and regulatory filings from the past decades.

Now, when preparing a newsletter or internal briefing, an agent can:

• Retrieve the latest fund updates and performance data.

• Surface comparable historical commentary from similar periods.

• Generate draft communications in the fund’s internal style guide.

This means faster turnaround for investor-facing materials and improved consistency across all communications.

Additional Applications

Beyond the core workflows, the fund’s technical team also experimented with AI agents that support software development and internal research:

The Pull Request Review Agent performs detailed code reviews across multiple programming languages.
The Meeting Note Agent structures transcripts and action items for cross-team distribution.
The Company Research Agent conducts deep web research to identify whether companies are developing or deploying AI, assigning confidence scores for investment analysis.

These smaller tools showcase how technical teams can prototype and scale AI agents rapidly within existing infrastructure on StackAI.

What's Next?

The fund plans to expand its use of agentic AI into additional domains, including accounting automation, audit preparation, and compliance monitoring, with the long-term goal of achieving real-time visibility into portfolio data and regulatory workflows.

StackAI continues to serve as the orchestration layer connecting internal APIs, unstructured documents, and secure data pipelines, synthesizing enterprise-grade governance with the flexibility of powerful automation. Want to see how StackAI help your enterprise save thousands of hours per year? Get a demo here.

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