An expert network is a service that finds an investor or a consultant a person with first-hand knowledge of a company or an industry, usually a former executive, and arranges a paid call between them. Newer expert networks are built as software. The platform finds the expert, schedules the call, transcribes it and makes the transcript searchable, so the conversation becomes data that others can buy. The main buyers are investment funds and consulting firms in the United States and the United Kingdom.
Why do investors pay for this? A company's public reports tell investors what the company chooses to say. A former sales director, a customer or a supplier can explain how the business actually works: why customers leave, how prices are set, and which rival is winning orders. One hour with such a person can save weeks of reading.
Consider an analyst at an investment fund in London who is studying a US-listed company that sells software to hospitals. She types her request into the platform: "a former sales leader who left the company within the last two years". The platform searches its database of experts, and also finds new ones by searching public career profiles. It contacts suitable people. Within a day, it shows her three profiles. She chooses a former regional sales director. The fund pays the platform a fee for the hour, often several hundred to over a thousand dollars, and the expert receives part of that fee.
The rules are strict, because these calls carry a risk of leaking inside information. Before each call, the expert confirms in writing that he will not share confidential information from a current or past employer, or important information that is not public. Many platforms do not let an expert talk about a company he left very recently. The platform's compliance team, the employees who check that the rules are followed, can record the call and review the transcript. In both the US and the UK, trading on inside information is a crime, and expert networks have featured in past insider trading cases.
After the call, software transcribes it, removes the expert's name and stores the transcript in a library. Later, other subscribers can search and read the transcript, for less than the price of a new call. This is how a call becomes a dataset. Call transcription and AI summaries produce the text and the summary. Financial research platforms increasingly include libraries of these transcripts, and an AI data analyst can answer questions across hundreds of transcripts at once.
An expert network is one kind of data vendor. The data it sells is the knowledge of people, recorded as text.