Monte is a project forecasting tool designed to accurately predict project completion dates using evidence-based scheduling. By analyzing historical project data, Monte runs extensive simulations to generate easy-to-read charts that identify probable end dates with associated confidence levels. This approach eliminates the need for guesswork and traditional estimation methods, providing a more reliable and data-driven timeline for project completion. Key Features and Functionality: - Evidence-Based Scheduling: Utilizes historical project data to run one million simulations, producing forecasts grounded in real-world performance. - Confidence Level Charts: Generates visual representations of probable project end dates, each accompanied by a confidence percentage, allowing teams to plan with greater certainty. - Adaptability to Changes: Quickly recalculates forecasts when project parameters change, such as the addition of new tasks, ensuring up-to-date and accurate timelines. - Automated Data Integration: Connects seamlessly with project management tools like Jira and GitHub to automatically extract the latest project data, streamlining the forecasting process. Primary Value and Problem Solved: Monte addresses the common challenge of accurately predicting project completion dates, a task often hindered by human estimation errors and unforeseen variables. By leveraging historical data and advanced simulations, Monte provides project managers and teams with reliable forecasts, enhancing planning accuracy and confidence. This data-driven approach reduces reliance on subjective estimates, mitigates risks associated with project delays, and facilitates more informed decision-making throughout the project lifecycle.