The data is public and structured
Fund regulation forces disclosure of domicile, geography exposure, derivatives usage, and delegation. That is exactly what a matching engine needs, and it sits in public prospectuses.
About
Built next to the buyer, not from a scraper demo.
The founder spent a product career with large insurance companies and asset managers across Asia. The real advantage is not the tech — scraping plus summarisation is commodity. It is domain relationships, credibility with the compliance buyer, and speed to a working pilot compared with a large FI’s internal build cycle.
Why asset managers first
Insurance product data is not
Policy wordings, reserving, and filings are far less standardised and far less public. A compelling public-data demo is much harder without internal access first.
The buyer already pays for data
Asset managers are culturally primed for third-party analytics. That shortens the path from a mapped circular to a paid pilot.
What we will not pretend is a moat
The scraper, the search queries, and the LLM call are replicable in months. What is defensible is the firm-specific mapping layer, the speed versus a 12–24 month internal cycle, and the switching cost once output is wired into a compliance calendar or GRC tool. Classification taxonomies help, but they are copyable if a client hires their own SME.
If you own the Taiwan book, we should be talking.
That includes a Hong Kong or Singapore desk covering North Asia distribution. Let’s talk.