Most deep-research reports are single-use and disposable, making the process slow, expensive, and wasteful. TESRAC changes that by treating completed research as a reusable, shareable artifact. It searches existing reports first. When fresh research is needed, we run research and adversarial agents in parallel, and a synthesis pass produces a structured report. Reports are saved, shareable, and discoverable. They also preserve their research context, so anyone can ask follow-up questions.
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Maker
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From finding the best robot vacuums to buy, to evaluating OLAP frameworks for work, using deep research saves me from opening dozens of tabs and manually cross-checking sources. But I just really hate how time consuming and expensive it can be. Therefore, I built TESRAC. It solves the two main hurdles that deep research currently has (time consuimg and expensive), at the cost of being in-personalized.