Conversational Search
Contextual and Targeted Search Experience
Aisera’s Conversational Search assistant allows users to search for information using natural language through conversations with a virtual assistant or a traditional search bar. It uses cognitive search models and advanced natural language processing (NLP) and understanding (NLU) technologies to understand the context and meaning of the user’s request and provide comprehensive and accurate search results. The user can interact with the system through an artificial intelligence chatbot interface that can have complex and human-like conversations.
Reduce implementation time
Onboard customers quickly – no explicit training or curation required
Improve search accuracy
Detect intent and context of queries to return accurate and relevant search results
Enhance user experience
Improve search functionality and user experience with NLP, NLU, and NLG for more human-like interactions
Autocomplete Search Suggestions
Provide predictive search query suggestions that allow users to search faster without the need to manually type every character
Personalized Search Experience
Provide search results based on user profile (example: location), known preference, and search history for a customized user experience
Semantic Search Using Large Language Models (LLMs)
Provide precise and accurate search results by leveraging the latest generation of natural language models called Large Language Models (LLMs) for an enhanced search experience
Realtime Reinforcement AI Learning
Utilize AI to continuously learn from past activities, interactions, and feedback to improve the accuracy of predictions and recommendations
Escalate to a Live Agent
Initiate a conversation with a bot or escalate to an agent for further assistance or in case of an unsatisfactory response
Access to 400+ Prebuilt Integrations
Connect instantly to your backend systems and leverage existing knowledge sources and content for a seamless experience
