Explainability
Explainability
Digitize risks with transparent and explainable reasoning
The Cytora platform’s Chain of Thought reasoning makes risk digitization explainable and steerable. Mandatory source lists for every value, accessible in the human review console mean extracted field values are always grounded in factual risk submission content. Voting based Confidence Scoring extracts every field value in 7 different ways, ensuring self-driven consistency and resulting in stable, repeatable outputs which unlock automation. Agentic multi-agent patterns go beyond simplistic prompt and completion paradigms, unlocking extraction from challenging scenarios. This includes large Excel files or PDF loss runs with claims that span page boundaries. Performance monitoring is automated and tracks accuracy, precision, recall, and F1 scores for continued autonomous training. Decision-ready risks are routed to downstream systems for decisioning.
Consistency
Digitize with consistency
Cytora digitizes submission data to fulfil your target schema, launching multiple parallel agents operating at different temperatures to digitize the same field, ensuring that the same submission inputs always provide the same outputs, every time.
Confidence
Confidence Scoring
Confidence scores are generated for every schema field based on the degree of inter-agent agreement, ensuring consistent results and automatically triggering human review where necessary.
Explainability
Chain of Thought reasoning
Chain of Thought reasoning provides human readable explanations of why field values were chosen including the provenance of extracted field candidates
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We are investing in digital capabilities to unlock scalable growth, Cytora enable us to streamline key workflows enhancing efficiency and effectiveness and further developing how we use data to drive decision making across the group and accelerating our profitable growth.”
Chief Operating Officer
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