From Surveys to Durable Data Assets
Engineering leader at Tegus on building a data platform for expert interviews
The real gap is not collecting survey responses, it is turning each survey into a durable data asset that compounds over time. Tegus built value by making every interview transcript searchable, linked to companies, and reusable across many clients. In contrast, mainstream survey tools mostly help teams design questionnaires and reuse question blocks, but they do not naturally turn repeated fieldwork into a shared, longitudinal library of structured market intelligence.
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Inside Tegus, the product play was already moving from one off calls to a reusable transcript library. The engineering work described elsewhere in the interview, like entity tagging and deep links into the exact section mentioning a company, shows the missing ingredient for surveys was not form building, it was knowledge graph style organization after collection.
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Survey platforms like Qualtrics do support reusable survey components, like library surveys, common question banks, and reusable answer choices. That solves authoring efficiency. It does not create a cross customer archive that lets an investor compare AI legal tools in March, April, and May and immediately trace changes back to respondent level evidence.
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This is why expert calls, surveys, and interviews are converging into one primary research stack. Dialectica already sells B2B surveys beside expert calls, and Office Hours describes the formats as collapsing into the same workflow. The winning product is likely the one that treats every response, whether spoken or clicked, as reusable research inventory.
The market is heading toward systems that run research continuously, not project by project. As AI makes it cheaper to launch surveys, transcribe interviews, and normalize answers, the advantage shifts to whoever best stores that output as living history, searchable by company, theme, date, and question, with each new study making the whole library smarter.