Becoming part of investor workflows
Engineering leader at Tegus on building a data platform for expert interviews
The real moat is not owning a destination site, it is becoming part of the investor’s native workflow where questions get answered inside Excel, internal research tools, and now AI agents. Tegus reached the limit of a portal model once transcript data started to look more like an input than a finished product. That is why API access and spreadsheet integration matter, even though they make copying, entitlement control, and pricing much harder.
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Tegus already moved in this direction with an Excel add in that lets analysts pull company data straight into models, instead of reading transcripts in one tab and manually updating numbers in another. That turns Tegus from a research stop into part of the actual analysis process.
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The broader platform play is visible after the AlphaSense acquisition. The combined product pairs expert transcripts with filings, broker research, financial models, internal documents, and ingestion APIs, so the winning product is the one that sits across all research inputs, not just the one with the best transcript library.
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This mirrors a broader shift in expert networks. Traditional firms sold high touch calls as a service, while newer products try to reduce friction and let insight flow into self serve software. Once customers expect AI systems to search, summarize, and act on research, closed portals become less defensible than workflow embedded data pipes.
The next step is for expert insight vendors to behave more like infrastructure for decision making. The companies that win will feed transcripts, metadata, and synthesized answers into customer tools securely, then capture more value by powering the full chain from research to model building to decision execution.