Canotera provides legal professionals with an AI-powered toolset for rapid case evaluation, predictive litigation insights, and strategic evidence discovery. By combining machine learning, natural language understanding, and conformal prediction techniques, it delivers explainable outcome forecasts (~85% accuracy), analogous case comparisons, and practical value estimations—all within a lawyer-friendly interface. The platform supports more informed decisions on case intake, valuation, resource deployment, and risk management.
Features and functions of Canotera include:
Outcome Prediction
Evaluates new disputes and forecasts litigation outcomes with approximately 85% accuracy, based on historical comparisons and algorithmic modelling. Predictions cover liability likelihood, expected award or settlement amounts, and process timelines.
Comparable Case Analysis
Identifies a concise set of analogous cases using a combination of large language models (LLMs), geometric machine learning, and conformal analysis. Inputs are standardized and scored for relevance; uncertainty is quantified transparently.
Evidence Discovery & Risk Insight
Enables rapid surface-level identification of critical evidence, case parallels, and structural factors—such as additional defendants, relevant patents, corporate relationships, and incident histories—that might be missed via manual review.
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