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Legal Citation Validation

Legal Citation Validation

Legal Language Simplification and Explanation

Legal Language Simplification and Explanation

B2B Terms Summarisation

B2B Terms Summarisation

Risk Assessment for Business Proposals

Risk Assessment for Business Proposals

Regulatory Update Impact Assessment

Regulatory Update Impact Assessment

Organisational Risk Tolerance Analysis for Contracts and Policies

Organisational Risk Tolerance Analysis for Contracts and Policies

Legal Document Summary

Legal Document Summary

Contract Clause Categorisation

Contract Clause Categorisation

Marketing Analyst

Personalised Product Recommendation

This agentic AI task generates personalised product recommendations - vital for e-commerce personalisation agents. The task configuration outlines how to:

  • Analyse user behaviour patterns and preferences

  • Identify relevant product associations and trends

  • Generate contextually appropriate suggestions

  • Rank recommendations by user relevance

  • Adapt suggestions based on interaction data


As a modular task, it integrates with catalogue and analytics systems, enabling AI agents to execute intelligent recommendation generation within existing e-commerce workflows. The task specification includes outputs for preference analysis, product matching, and recommendation optimization, adaptable across various retail contexts and user segments.

Try this Task

Try this Task

Try this Task

Try this Task

Example outputs:

{
  "recommended_products": [
    "PROD123",
    "PROD456",
    "PROD789",
    "PROD101",
    "PROD202"
  ],
  "recommendation_reasons": [
    "Similar to recently viewed running shoes",
    "Complementary to user's recent purchase of fitness tracker",
    "Trending product in user's frequently browsed 'Outdoor Gear' category",
    "Based on positive reviews from users with similar purchase history",
    "Seasonal recommendation aligned with user's interest in winter sports"
  ],
  "user_affinities": [
    "Athletic footwear",
    "Fitness technology",
    "Outdoor activities",
    "Winter sports equipment"
  ],
  "recommendation_strategy": "Mixed strategy: Past behaviour, complementary products, and seasonal trends",
  "confidence_scores": [
    "95",
    "88",
    "82",
    "79",
    "75"
  ],
  "diverse_recommendations": true,
  "personalisation_level": "High",
  "additional_insights": "User shows a strong preference for premium athletic brands and tends to make purchases in preparation for seasonal activities. They are also likely to be interested in new fitness technology products."

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Legal Citation Validation

Legal Citation Validation