The methodology is designed so that important business questions do not stop at a single answer or a single starting assumption.
A single model can reinforce an initial assumption, miss an important risk or present a conclusion with more certainty than the available evidence warrants. Several separate perspectives do not turn a conclusion into a fact, but they help you see the question more completely.
The process consists of separate analyses, an anonymous evaluation and ranking of the answers, and a final synthesis. At each stage, the aim is to distinguish facts, assumptions, arguments, risks and open questions.
Each perspective is given a clearly defined analytical style before it answers, for example a focus on risk, on numbers and cash flow, or on long-term strategy. That style is based on recognizable, publicly known ways of thinking from relevant fields such as business strategy, negotiation and risk management, not on training on private sources. It does not represent the views or involvement of any specific individual. It is a stylized analytical framework that helps examine the same question from several angles.
The system supports 42 languages. The final report is prepared in the language of the request, with the limits of the service clearly stated.
Zero Data Retention is required when requests are routed to providers, with documented exceptions (see the Confidentiality page). Logging of prompt and response content, forwarding to external monitoring platforms, training on request data and prompt publishing are all disabled in the active settings. Technical metadata may be processed to operate and secure the service.
Agreement among multiple AI perspectives is not the same as fact-checking. Conclusions rely on the information you provide, so we recommend verifying key facts and figures before you decide.
Details on confidentiality, zero data retention and the ban on model training are in one place: Confidentiality.
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