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Wisdom AI launches Proactive Agents that use  a “knowledge fabric” to find answers from human workers;  these automated data analysts monitor KPIs, detect anomalies and deliver natural language insights

September 8, 2025 //  by Finnovate

AI-native data insights startup Wisdom AI has launched Proactive Agents that act like automated data analysts and work around the clock to proactively learn, prepare analyses and reports and make decisions based on the insights they surface. The new agents can carry out data analysis work without human supervision, freeing up human workers to focus on more strategic work, the company said. The startup uses AI “reasoning” models in combination with a knowledge fabric, uniting disconnected resources for deeper analysis with added context in order to generate more meaningful insights. The Proactive Agents utilize the knowledge fabric to find answers to questions from human workers, such as marketing or sales team personnel. Alternatively, they can simply wait in the background, keeping a watchful eye on key business metrics, and issue alerts when certain milestones, thresholds or targets are met. They work by autonomously scanning and analyzing KPIs to detect meaningful deviations. When this happens, they’ll carry out an in-depth analysis to explain why it occurred, and then provide a simple, natural language summary for human decision-makers. This can help businesses to make decisions faster, because they won’t have to wait until a human data analyst finds the time to perform the necessary investigation. One of the main advantages of Wisdom AI’s Proactive Agents is their ability to learn continuously as they perform their work, remembering earlier analyses they’ve carried out, including what caused certain anomalies to occur. They’re programmed to flag any meaningful shifts in business metrics and then dig deeper into the reasons why by carrying out exhaustive root cause analysis. As part of this, they’ll identify which segments of the business were affected, over how long a time frame. And they’ll dig up evidence to support their findings, so they can be verified by any human worker. Once the agents are ready to report their findings, they’ll transform the patterns they’ve identified into a concise, actionable alert, complete with any useful charts, SQL queries and recommendations, the company said.

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Category: AI & Machine Economy, Innovation Topics

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