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Solutions for the
data-driven enterprise

Enabling everyone to run AI with certainty

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As

teams across industries

adopt AI to solve the most pressing business problems, WhyLabs enables them to operate with certainty by providing model monitoring, preventing costly model failures, and facilitating cross-functional collaboration.

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E-commerce

  • Recommendations
  • Personalization
  • Inventory management
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Logistics

  • Warehouse optimization
  • Supply chain planning
  • Peak hours prediction
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Cybersecurity

  • Network traffic classification
  • Network anomaly detection
  • User/machine behavioral analysis
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Real Estate

  • Personalization
  • Property Market Value forecasting
  • Advanced Property Analysis
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Healthcare

  • Discharge planning
  • Capacity planning
  • Medical record extraction
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Telecommunications

  • Customer churn prediction
  • Personalization
  • Fraud detection

A single platform for any use case

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Power AI operations for structured and unstructured data
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Ranking and Recommendations
  • Ensure that the model makes recommendations accurately and consistently
  • Prevent model decay caused by concept drift and data quality issues
  • Increase ROI for marketing and advertising spend
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Forecasting
  • Equip your team with tools that alert about forecasting bias
  • Prevent forecasting bias caused by data quality and seasonal drifts
  • Increase ROI by continuously improving model performance across edge cases
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Document understanding
  • Ensure consistent performance across information extraction pipelines
  • Prevent pipeline failures caused by concept drift and data quality
  • Maintain trust in model accuracy with customers and end users
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Image understanding
  • Prevent bias and failures caused by data drift and data quality
  • Ensure consistent performance across all data segments and hardware types
  • Maintain trust in model accuracy with customers and end users

Running AI is a Team Sport

Surface the right insights to the right team members
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Data Scientists & ML Engineers

  • Spend less time building tools, spend more time building and improving AI applications
  • Speed up the model development process by automating training data validation with WhyLogs
  • Equip production pipelines with state-of-the-art data logging and monitoring techniques
  • Prevent model failures by catching data quality, data drift and concept drift problems proactively
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Product Managers & Team Leads

  • Gain customer trust by catching model failures before they affect user experience
  • Reduce technical debt and maintenence costs by streamlining model operations
  • Connect model performance metrics to core business KPIs and track everything through a unified interface
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Executives & Senior Leadership

  • Gain and retain trust with stakeholders by eliminating failures and undesirable AI predictions
  • Realize ROI from AI investment by reducing model development cycles and technical debt
  • Gain transparency into data and model health through a unified, intuitive interface
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Run AI With Certainty

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