Expert Calls Become Premium Data
Engineering leader at Tegus on building a data platform for expert interviews
AI shifts advantage away from who can read public filings fastest, and toward who can capture, organize, and reuse what knowledgeable people know before it is written down. Tegus built around that idea by turning expert calls into a searchable dataset, then linking those transcripts to models and filings so an investor could move from a filing, to an expert view, to a model change inside one workflow.
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The core product was not the live call by itself, but the library created after the call. Tegus priced calls close to pass through cost, while the higher value product was subscription access to transcripts. That made expert knowledge reusable across many users, unlike a traditional brokered call that disappears once it ends.
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BamSEC and Canalyst mattered because they sit right next to the investment decision. A hedge fund analyst can read what an expert says about demand, compare it with company filings in BamSEC, then adjust assumptions in a Canalyst model. AI makes the cross linking, summaries, and question extraction much faster, but the raw edge still comes from the human source.
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This also explains why transcript quality matters more as AI improves. Public information and basic summarization get cheaper for everyone, so differentiation shifts to better questions, better experts, and tighter workflow integration. That is why newer players like Office Hours focus on reducing expert side friction, while AlphaSense uses Tegus content as part of a larger proprietary research stack.
The market is moving toward platforms that combine proprietary human insight with AI search and structured datasets. Over time, expert calls become less of a standalone service and more of a premium data layer inside research software, where the winners are the ones that can turn conversations into trusted, workflow ready intelligence faster than anyone else.