{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_marple-ai","slug":"marple-ai","name":"Marple AI","type":"product","url":"https://www.marpledata.com","page_url":"https://unfragile.ai/marple-ai","categories":["data-analysis"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_marple-ai__cap_0","uri":"capability://data.analysis.automated.time.series.decomposition","name":"automated time series decomposition","description":"Automatically decomposes time series data into trend, seasonal, and residual components without requiring manual statistical configuration. Eliminates the need to write decomposition code from scratch.","intents":["I want to understand the underlying patterns in my time series data quickly","I need to separate trend from seasonality without learning statistical methods","I want to visualize components of my time series without writing code"],"best_for":["product analysts","supply chain researchers","non-technical data users"],"limitations":["only works with univariate time series","may not handle irregular time intervals well","limited customization of decomposition parameters"],"requires":["time-indexed numerical data","regular or semi-regular time intervals"],"input_types":["CSV","structured time series data"],"output_types":["visualizations","decomposed component data"],"categories":["data analysis","time series"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_1","uri":"capability://data.analysis.anomaly.detection.in.time.series","name":"anomaly detection in time series","description":"Identifies statistical outliers and anomalies in time series data using built-in algorithms. Flags unusual patterns without requiring manual threshold setting or algorithm selection.","intents":["I need to find unexpected spikes or drops in my data","I want to detect system failures or unusual events automatically","I need to flag data quality issues in my time series"],"best_for":["operations teams","quality assurance analysts","supply chain managers"],"limitations":["may produce false positives in highly volatile data","limited control over sensitivity thresholds","assumes normal behavior patterns exist"],"requires":["historical time series data","sufficient data points to establish baseline"],"input_types":["CSV","time series data"],"output_types":["flagged anomalies","anomaly scores","visualizations with highlighted points"],"categories":["data analysis","time series","quality assurance"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_2","uri":"capability://data.analysis.time.series.forecasting","name":"time series forecasting","description":"Generates future value predictions for time series data using automated model selection and training. Produces forecasts with confidence intervals without requiring users to choose or tune forecasting algorithms.","intents":["I need to predict future values in my time series","I want to forecast demand or inventory levels","I need to estimate future trends for planning purposes"],"best_for":["product analysts","supply chain planners","business forecasters"],"limitations":["forecast accuracy degrades for long-term predictions","struggles with structural breaks or regime changes","limited ability to incorporate external variables"],"requires":["historical time series data","sufficient historical data for pattern learning"],"input_types":["CSV","time series data"],"output_types":["forecast values","confidence intervals","forecast visualizations"],"categories":["data analysis","time series","predictive analytics"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_3","uri":"capability://collaboration.collaborative.analysis.workspace","name":"collaborative analysis workspace","description":"Provides a shared environment where multiple team members can view, annotate, and discuss time series analyses in real-time. Enables teams to collaborate without exporting data or switching between tools.","intents":["I want my team to review and comment on my analysis","I need to share findings with stakeholders without creating separate reports","I want to discuss data patterns with colleagues in one place"],"best_for":["research teams","cross-functional product teams","academic collaborators"],"limitations":["collaboration features may be limited compared to dedicated platforms","unclear version control for analyses","real-time sync reliability unknown"],"requires":["user accounts","shared workspace access","internet connection"],"input_types":["analyses","annotations","comments"],"output_types":["shared workspace","commented analyses","discussion threads"],"categories":["collaboration","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_4","uri":"capability://data.visualization.interactive.time.series.visualization","name":"interactive time series visualization","description":"Generates interactive charts and graphs for time series data with built-in exploration tools like zooming, panning, and hover details. Allows users to explore data patterns visually without coding.","intents":["I want to explore my time series data visually","I need to zoom into specific time periods to see details","I want to create presentation-ready visualizations quickly"],"best_for":["analysts","business users","researchers"],"limitations":["limited customization of visual styling","may not handle extremely large datasets efficiently","export options unclear"],"requires":["time series data","web browser"],"input_types":["CSV","time series data"],"output_types":["interactive charts","static visualizations","exported images"],"categories":["data visualization","time series"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_5","uri":"capability://data.analysis.statistical.summary.generation","name":"statistical summary generation","description":"Automatically calculates and displays key statistical metrics for time series data including mean, variance, autocorrelation, and seasonality strength. Provides instant statistical context without manual calculation.","intents":["I want to understand the statistical properties of my data","I need to check if my data has strong seasonality","I want to see correlation patterns in my time series"],"best_for":["analysts","researchers","data scientists"],"limitations":["limited to univariate statistics","no multivariate correlation analysis","may not handle missing data well"],"requires":["time series data"],"input_types":["CSV","time series data"],"output_types":["statistical summaries","metric tables","statistical visualizations"],"categories":["data analysis","statistics"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_6","uri":"capability://data.preparation.data.import.and.preprocessing","name":"data import and preprocessing","description":"Handles loading time series data from various sources and performs basic preprocessing like handling missing values, resampling, and time index alignment. Prepares raw data for analysis without manual data cleaning code.","intents":["I want to load my CSV file and start analyzing immediately","I need to handle missing values in my time series","I want to resample my data to different time frequencies"],"best_for":["analysts","researchers","business users"],"limitations":["limited preprocessing options compared to Pandas","may not handle complex data quality issues","unclear support for multiple file formats"],"requires":["data file","properly formatted time index"],"input_types":["CSV","potentially other structured formats"],"output_types":["cleaned time series data","preprocessed dataset"],"categories":["data preparation","data engineering"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_7","uri":"capability://data.analysis.pattern.recognition.and.insights.extraction","name":"pattern recognition and insights extraction","description":"Automatically identifies and highlights significant patterns, trends, and insights in time series data. Surfaces key findings without requiring manual pattern analysis or statistical testing.","intents":["I want to understand what patterns exist in my data","I need key insights extracted from my time series automatically","I want to know what's driving changes in my data"],"best_for":["business analysts","product managers","researchers"],"limitations":["insights may be generic or obvious","limited explainability of how patterns were identified","may miss domain-specific patterns"],"requires":["time series data","sufficient data for pattern detection"],"input_types":["time series data"],"output_types":["insight summaries","pattern descriptions","highlighted visualizations"],"categories":["data analysis","insights"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_marple-ai__cap_8","uri":"capability://pricing.model.freemium.exploratory.analysis","name":"freemium exploratory analysis","description":"Provides a free tier with functional time series analysis capabilities for exploratory work and testing. Allows users to validate workflows and learn the platform before committing to paid plans.","intents":["I want to try time series analysis without paying","I need to test if this tool works for my use case","I want to explore my data before deciding on a tool"],"best_for":["researchers","students","budget-conscious teams","tool evaluators"],"limitations":["free tier may have feature restrictions","unclear data size limits","support may be limited for free users"],"requires":["user account","internet connection"],"input_types":["time series data"],"output_types":["analyses","visualizations","insights"],"categories":["pricing model","accessibility"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["time-indexed numerical data","regular or semi-regular time intervals","historical time series data","sufficient data points to establish baseline","sufficient historical data for pattern learning","user accounts","shared workspace access","internet connection","time series data","web browser"],"failure_modes":["only works with univariate time series","may not handle irregular time intervals well","limited customization of decomposition parameters","may produce false positives in highly volatile data","limited control over sensitivity thresholds","assumes normal behavior patterns exist","forecast accuracy degrades for long-term predictions","struggles with structural breaks or regime changes","limited ability to incorporate external variables","collaboration features may be limited compared to dedicated platforms","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.39999999999999997,"quality":0.77,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.857Z","last_scraped_at":"2026-04-05T13:23:42.546Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=marple-ai","compare_url":"https://unfragile.ai/compare?artifact=marple-ai"}},"signature":"JhpoPOVEoa6sYEiBFS3K33VhUfOXp5zxnVo8jwRjDdfoIYtZXaryugyy/JJmlk0hkbBYzxoTg6Xx6S3FcRPsBA==","signedAt":"2026-06-21T01:25:22.533Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/marple-ai","artifact":"https://unfragile.ai/marple-ai","verify":"https://unfragile.ai/api/v1/verify?slug=marple-ai","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}