Recommender System
Make better choices in complex situations.
AI-powered decision-making
Enable your employees to make faster, better decisions with AI that learns from past data and continuously improves based on user feedback
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Deeper insights
Gain a new understanding of company behavior powered by hybrid models that combine classical machine learning and deep learning.
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Continuous improvement
Optimize results with employee oversight and leverage feedback for ongoing system learning.
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Built-in transparency
Embedded explainability shows users how and why the system made each recommendation, enabling trust with users.
The Element AI Difference
State-of-the-art recommender system that can be customized, easily deployed and fine-tuned on client data
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Customizable
Can be adapted to a specific use case by leveraging your company data as well as our powerful transfer learning and generative models.
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End-to-end
Seamless integration with your stack and other AI capabilities enables new synergies across different signals and processes, generating more relevant outputs and greater impact.
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Flexible
Supported by deep technical expertise, infrastructure and tools, systems can be rapidly trained and deployed, either on-prem or cloud.
Key Benefits
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Improve process efficiency and automation
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Drive customer satisfaction, for example with new personalized offers
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Increase revenue with better decision-making
Recommender System for Insurance
The EAI Recommender System component can be used to increase accuracy and consistency in the underwriting process by making coverage recommendations to underwriters based on coverage decisions from previous submissions with similar attributes.
How it works together with
time-series forecasting
Combined with state-of-the-art, dynamic forecasting capabilities, our recommender systems can provide insights based on past data as well as on future predictions, enabling even more robust decision-making.
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