Personalization and recommendation systems
Custom-Built-AI
Recommendation systems that adapt to behavior, context and real-time interactions.
Challenge
Generic recommendation approaches could not reflect the nuance of user context, intent or evolving behaviour.
Solution
Tigient engineered custom recommendation models and orchestration flows that adapt outputs in real time based on behaviour, patterns and contextual signals.
Impact
Higher relevance
Improved retention potential
More adaptive user journeys
Capability mix
Recommendation enginesBehavioral intelligenceRealtime adaptationAI orchestration