Chris Halanish calls the $100 trillion asset management industry a stack of “human duct tape.” The CEO of Hanover Park argues that institutional data is held hostage by service providers using QuickBooks and Excel, creating a fragile system where a fund accountant's departure can wipe out its operational memory. He proposes replacing it with AI agents equipped with long-term memory to learn each fund’s specific legal quirks and accounting rules.
This is a move beyond selling software. Halanish is building an AI-native services company that owns the outcome. The goal is to automate the unsexy core systems of record - capital calls, profit-and-loss allocations - rather than just providing a tool for human operators.
The technical barrier was ontology. Mapping the complex web of relationships between legal entities, limited partnership agreements, and portfolio companies made migrating a fund like Blackstone a two-year project. Halanish claims this prevented modernization until roughly six months ago.
Hanover Park uses long-horizon agents to clean financial data at scale, ingesting hundreds of thousands of legacy documents to extract governing rules. In one case, his team migrated a fund with 20 entities in six days - a task his engineers considered impossible a year prior. The shift became viable with models like OpenAI’s Opus series, which handle massive context windows and maintain accuracy across decades.
"It's human duct tape... it's QuickBooks, it's Bill.com, it's Excel."
- Chris Halanish, This Week in Startups
This automation enables a pricing revolution. The era of charging for software seats is fading. While Figma’s Dylan Field built trust through seat transparency in 2020, new AI-native firms like Hanover Park are charging basis points on assets under management.
Outcome-based pricing aligns incentives. Legacy SaaS vendors profited from “shelfware” - seats paid for but unused. Charging based on AUM or value created makes the AI provider a growth partner. Hanover Park grew from $1 billion to $20 billion in assets under management over 15 months with a 50-person team, focusing on making CFOs “raving fans” rather than sharing aggregated data.
The model abstracts the labor. The AI agent becomes the institutional memory, eliminating the volatility of human turnover. For a system managing a century’s wealth, continuity is now automated.
