Expert Networks Becoming Transcript Platforms

Tegus changed the business model from selling one expert call at a time to selling a reusable knowledge asset. Instead of making money mainly when a client booked a call, it used each call to create a transcript that could be searched, tagged, summarized, and sold again across many seats. That turned expert network operations into content production, and made the transcript library, not the expert roster, the core product.

• Traditional expert networks act more like brokers. A client asks for a former executive or customer, the network finds one, schedules the call, and gets paid for that interaction. Tegus kept the call flow, but treated the transcript as the lasting asset, with subscription seats around $25K and call fees closer to pass through cost.
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• Once transcripts became the product, software mattered much more. Tegus could tag every company named in a call, link users to the exact relevant passage, generate summaries, and surface patterns across dozens of interviews. That made a messy hour long conversation behave more like a searchable proprietary database.
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• This is why Tegus fit so naturally inside AlphaSense. AlphaSense already sold search across filings, broker research, and earnings calls. Tegus added a proprietary dataset that users could query the same way, and AlphaSense now markets expert transcripts, models, and public documents as one combined research workflow.
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The category is moving toward platforms that turn human conversations into indexed, machine readable research inventory. That favors companies that can both source high quality experts and package the output into software workflows. Over time, the winners look less like call brokers and more like proprietary data platforms with expert generation built in.