Ride the LLM Wave with
SearchUnify
Make Large Language Models (LLMs) a part of your Customer
Support Ecosystem with SearchUnify
A large language model (LLM) is a powerful neural network that has been trained on a massive corpus of natural language data to generate human-like responses. These models use deep-learning algorithms to perform various tasks, such as language translation, text summarization, chatbot conversations, and more. Some well-known LLM models include OpenAI's ChatGPT, Google's BERT, and Facebook's RoBERTa.
Organizations are in a race to adopt Large Language Models. And while, organizations stand to gain a lot of productivity improvements
through LLMs, when a user question is directly sent to the open-source LLM,
there is increased potential for hallucinated responses based on the generic
dataset the LLM was trained on.
This is where SearchUnify’s Federated Retrieval
Augmented Generation approach to LLMs comes into play.
Helps enhance the user input with context retrieved from a 360-degree view of the enterprise knowledge base. This helps the LLM-integrated SearchUnify products to more readily generate a contextual response with factual content.
Involves accessing relevant information or responses from a predefined set of knowledge or data. This is done using various methods such as keyword matching, semantic similarity, or advanced retrieval algorithms.
Involves generating human-like responses or outputs based on the retrieved information or context, across SearchUnify’s suite of products. This is achieved using techniques like language modeling or neural networks.
We use multi-layered security to ensure sensitive information isn’t shared with all users even in the same organization.
We utilize bias-mitigation techniques, audit mechanisms, and relevant engineering to curtail the bias associated with LLM, thus maintaining credibility and trust.
We understand domain-specific context, which eliminates the LLM challenges related to limited expertise.
We look past semantics and decipher real human emotions. This enhances our scope to handle a range of text and language domains.
Our LLM-integrated search and tools are suitable for deployment on different support channels, such as the web, chatbots, and voice assistants.
![SearchUnify’s [F]RAG Approach - Enabling Context-aware, Personalized and Efficient Conversational AI Experiences](https://www.searchunify.com/wp-content/uploads/2023/08/searchunifys-frag-approach-enabling-context-aware-personalized-and-efficient-conversational-ai-experiences.jpg)
