Agents That Know Every Customer

Real-time personalization powered by persistent customer memory. Recommendations improve with every interaction.

The Problem

Cold Start

Every session starts fresh. No memory of past preferences.

Batch Updates

Recommendation models retrain nightly. Miss real-time signals.

Low Conversion

Generic recommendations drive generic results.

The HatiData Fix

Customer Memory

Every browse, cart, and purchase stored with semantic context.

Real-Time Ranking

semantic_rank() scores products against live customer intent.

Continuous Learning

Memory grows with every interaction. No batch retraining.

See It in Action

SELECT p.product_id, p.name, p.category,
       semantic_rank(m.embedding, 'organic skincare routine') AS relevance
FROM products p
JOIN_VECTOR customer_memories m
  ON semantic_match(m.embedding, 'organic skincare routine', 0.65)
ORDER BY relevance DESC LIMIT 12;

35%

higher conversion

<100ms

personalization latency

28%

larger basket size

Related Use Cases

Customer Support

End the amnesia loop. Your support agent recalls every past interaction, preference, and resolution — across sessions.

View use case

Manufacturing & Quality Control

Agents correlate sensor data with historical defect patterns. Semantic triggers catch quality drift before defects ship.

View use case

Gaming & Virtual Worlds

Non-player characters with persistent memory create emergent narratives. Branching storylines test in isolation before going live.

View use case

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