NEW! Download Gartner® Report: How to Improve and Optimize Retrieval Augmented Generation Systems. Get Started.
NEW! Download Gartner® Report: How to Improve and Optimize Retrieval Augmented Generation Systems. Get Started.
NEW! Download Gartner® Report: How to Improve and Optimize Retrieval Augmented Generation Systems. Get Started.
SearchAI Private LLM
SearchAI Private LLM
SearchAI Private LLM
High-Performance LLM Inference with Purely CPUs
High-Performance LLM Inference with Purely CPUs
High-Performance LLM Inference with Purely CPUs
Enable AI Assistants easily and securely on your organization’s private data.
Enable AI Assistants easily and securely on your organization’s private data.
Enable AI Assistants easily and securely on your organization’s private data.
Schedule a Private Demo
Schedule a Private Demo
Fixed Cost
Fixed Cost
Significantly reduce costs and complexity; our solutions easily integrate with existing hardware and virtual servers.
Highly Scalable
Highly Scalable
Deploy AI models that are scalable across your organization and unlock the full potential of your data.
Secure & Private
Secure & Private
Keep your model, your inference requests and your data sets within the security domain of your organization.
Optimized for RAG
Optimized for RAG
Set up AI assistants and conversational chatbots using your own data directly on the SearchAI platform.
What is RAG?
RAG stands for Retrieval-Augmented Generation. It is an approach that combines the capabilities of large language models (LLMs) with information retrieval from external data sources. Here’s how it works:
01
01
01
Asking Questions
Asking Questions
Asking Questions
A user starts a conversation with the chatbot through a question. The user question is converted into a semantic retrieval query.
A user starts a conversation with the chatbot through a question. The user question is converted into a semantic retrieval query.
A user starts a conversation with the chatbot through a question. The user question is converted into a semantic retrieval query.
02
02
02
Fetching Answers
Fetching Answers
Fetching Answers
The retrieval component searches through a corpus of documents or data sources to find the most relevant information.
The retrieval component searches through a corpus of documents or data sources to find the most relevant information.
The retrieval component searches through a corpus of documents or data sources to find the most relevant information.
03
03
03
Creating Context
Creating Context
Creating Context
The retrieved information, along with the user question, is passed to a large language model (LLM) for processing.
The retrieved information, along with the user question, is passed to a large language model (LLM) for processing.
The retrieved information, along with the user question, is passed to a large language model (LLM) for processing.
04
04
04
Delivering Results
Delivering Results
Delivering Results
The language model generates a final answer by synthesizing and reasoning over the retrieved information.
The language model generates a final answer by synthesizing and reasoning over the retrieved information.
The language model generates a final answer by synthesizing and reasoning over the retrieved information.
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What is RAG?
RAG stands for Retrieval-Augmented Generation. It is an approach that combines the capabilities of large language models (LLMs) with information retrieval from external data sources. Here’s how it works:
What is RAG?
RAG stands for Retrieval-Augmented Generation. It is an approach that combines the capabilities of large language models (LLMs) with information retrieval from external data sources. Here’s how it works:
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This allows RAG models to provide more factual and up-to-date responses by leveraging external knowledge sources, rather than being limited to what’s contained in the language model’s training data.
This allows RAG models to provide more factual and up-to-date responses by leveraging external knowledge sources, rather than being limited to what’s contained in the language model’s training data.
This allows RAG models to provide more factual and up-to-date responses by leveraging external knowledge sources, rather than being limited to what’s contained in the language model’s training data.
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Setting Up RAG ChatBots
Setting Up RAG ChatBots efficiently and Securely
Setting Up RAG ChatBots efficiently and securely
.
SearchAI provides a single platform for deploying RAG chatbots on your data, making it easy to leverage the power of RAG without compromising data privacy or security. Set up in a few simple steps.
Data Ingestion
Import your proprietary data sources or document corpora into the SearchAI platform. This could include manuals, legal documents, knowledge bases, etc.
ChatBot Interface Setup
Setup your chatbot for the private data using SearchAI.
Index Creation
Build efficient search indexes over your data to enable fast retrieval.
Query Handling
When a user query comes in, SearchAI retrieves relevant information and passes it to your LLM to generate a final response.
Model Integration
Connect and use SearchAI Private LLM.
Testing & Refinement
Evaluate your chatbot’s performance, fine-tune prompts and make adjustments to improve accuracy.
Deployment
Once finalized, deploy your private RAG chatbot on your own hardware or SearchAI’s secure cloud infrastructure.
Get Started with RAG
Data Ingestion
Data Ingestion
Import your proprietary data sources or document corpora into the SearchAI platform. This could include manuals, legal documents, knowledge bases, etc.
Import your proprietary data sources or document corpora into the SearchAI platform. This could include manuals, legal documents, knowledge bases, etc.
ChatBot Interface Setup
ChatBot Interface Setup
Setup your chatbot for the private data using SearchAI.
Setup your chatbot for the private data using SearchAI.
Index Creation
Index Creation
Build efficient search indexes over your data to enable fast retrieval.
Build efficient search indexes over your data to enable fast retrieval.
Query Handling
Query Handling
When a user query comes in, SearchAI retrieves relevant information and passes it to your LLM to generate a final response.
When a user query comes in, SearchAI retrieves relevant information and passes it to your LLM to generate a final response.
Model Integration
Model Integration
Connect and use SearchAI Private LLM.
Connect and use SearchAI Private LLM.
Testing & Refinement
Testing & Refinement
Evaluate your chatbot’s performance, fine-tune prompts and make adjustments to improve accuracy.
Evaluate your chatbot’s performance, fine-tune prompts and make adjustments to improve accuracy.
Deployment
Deployment
Once finalized, deploy your private RAG chatbot on your own hardware or SearchAI’s secure cloud infrastructure.
Once finalized, deploy your private RAG chatbot on your own hardware or SearchAI’s secure cloud infrastructure.
Get Started with RAG
Get Started with RAG
The Benefits of RAG
There are several key benefits to using a RAG approach:
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The Benefits of RAG
The Benefits of RAG
There are several key benefits to using a RAG approach:
There are several key benefits to using a RAG approach:
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Improved Accuracy & Relevance
Access to Up-to-Date Information
Domain Knowledge Expansion
No Hallucination
Enhanced Reasoning Capabilities
By retrieving information from pre-defined authoritative sources, RAG can provide more factual and reliable responses than LLMs alone.
Improved Accuracy & Relevance
Access to Up-to-Date Information
Domain Knowledge Expansion
No Hallucination
Enhanced Reasoning Capabilities
By retrieving information from pre-defined authoritative sources, RAG can provide more factual and reliable responses than LLMs alone.
Improved Accuracy & Relevance
By retrieving information from pre-defined authoritative sources, RAG can provide more factual and reliable responses than LLMs alone.
Access to Up-to-Date Information
Domain Knowledge Expansion
No Hallucination
Enhanced Reasoning Capabilities
Improved Accuracy & Relevance
By retrieving information from pre-defined authoritative sources, RAG can provide more factual and reliable responses than LLMs alone.
Access to Up-to-Date Information
Domain Knowledge Expansion
No Hallucination
Enhanced Reasoning Capabilities
Schedule Private Demo
Modernize Customer Service with AI Assistants
Implementing AI assistants on your website or customer portal can revolutionize your customer service operations, providing 24/7 support, instant responses, and personalized experiences.
How to Calculate the Total Cost of RAG-Based Solutions
Calculating a 3-5 year total cost of ownership is crucial for RAG solutions. Generative AI requires strategic planning to manage costs and ensure ROI, including aspects like talent, infrastructure, software, data and support.
Elevate Your Adobe Experience Manager (AEM) Site with AI Chatbots
AEM sites can now incorporate Generative AI-based chatbots to meet customer demands for quick access to sales, customer service or knowledge management information.
Modernize Customer Service with AI Assistants
Implementing AI assistants on your website or customer portal can revolutionize your customer service operations, providing 24/7 support, instant responses, and personalized experiences.
How to Calculate the Total Cost of RAG-Based Solutions
Calculating a 3-5 year total cost of ownership is crucial for RAG solutions. Generative AI requires strategic planning to manage costs and ensure ROI, including aspects like talent, infrastructure, software, data and support.
Elevate Your Adobe Experience Manager (AEM) Site with AI Chatbots
AEM sites can now incorporate Generative AI-based chatbots to meet customer demands for quick access to sales, customer service or knowledge management information.
Modernize Customer Service with AI Assistants
Implementing AI assistants on your website or customer portal can revolutionize your customer service operations, providing 24/7 support, instant responses, and personalized experiences.
How to Calculate the Total Cost of RAG-Based Solutions
Calculating a 3-5 year total cost of ownership is crucial for RAG solutions. Generative AI requires strategic planning to manage costs and ensure ROI, including aspects like talent, infrastructure, software, data and support.
Elevate Your Adobe Experience Manager (AEM) Site with AI Chatbots
AEM sites can now incorporate Generative AI-based chatbots to meet customer demands for quick access to sales, customer service or knowledge management information.
Use Cases for SearchAI Private LLM
Use Cases for SearchAI Private LLM
The benefits of AI assistants range from increased customer experience and faster service ticket responses to higher employee output and increased organizational knowledge. How will you leverage SearchAI to grow your organization?
The benefits of AI assistants range from increased customer experience and faster service ticket responses to higher employee output and increased organizational knowledge. How will you leverage SearchAI to grow your organization?
Government
Government
Government
Maintaining compliance clarity.
Maintaining compliance clarity.
Maintaining compliance clarity.
A government agency launched a chatbot for tax professionals to ask questions on complex laws, rulings and decisions.
A government agency launched a chatbot for tax professionals to ask questions on complex laws, rulings and decisions.
A government agency launched a chatbot for tax professionals to ask questions on complex laws, rulings and decisions.
Get Started with RAG
Get Started with RAG
Get Started with RAG
Manufacturing
Manufacturing
Manufacturing
Aligning organizational knowledge.
Aligning organizational knowledge.
Aligning organizational knowledge.
A manufacturing facility needs to find information from product manuals in an expedited manner.
A manufacturing facility needs to find information from product manuals in an expedited manner.
A manufacturing facility needs to find information from product manuals in an expedited manner.
Finance
Finance
Finance
Expediting customer support responses.
Expediting customer support responses.
Expediting customer support responses.
A finance department can query information about purchase orders and invoices for efficient customer support.
A finance department can query information about purchase orders and invoices for efficient customer support.
A finance department can query information about purchase orders and invoices for efficient customer support.
Schedule Strategy Session
Schedule Strategy Session
See For Yourself
See For Yourself
See For Yourself
Discover the strategic benefits of RAG — get started with a private, customized demo with your own data.
Discover the strategic benefits of RAG — get started with a private, customized demo with your own data.
Discover the strategic benefits of RAG — get started with a private, customized demo with your own data.
Schedule A Private Demo
Schedule A Private Demo
Enhance your users’ digital experience.
We build AI-driven software to help organizations leverage their unstructured and structured data for operational success.
4870 Sadler Road, Suite 300, Glen Allen, VA 23060 sales@searchblox.com | (866) 933-3626
Still learning about AI? See our comprehensive Enterprise Search RAG 101 and ChatBot 101 guides.
©2024 SearchBlox Software, Inc. All rights reserved.
Enhance your users’ digital experience.
We build AI-driven software to help organizations leverage their unstructured and structured data for operational success.
4870 Sadler Road, Suite 300, Glen Allen, VA 23060 sales@searchblox.com | (866) 933-3626
Still learning about AI? See our comprehensive Enterprise Search RAG 101 and ChatBot 101 guides.
©2024 SearchBlox Software, Inc. All rights reserved.
Enhance your users’ digital experience.
We build AI-driven software to help organizations leverage their unstructured and structured data for operational success.
4870 Sadler Road, Suite 300, Glen Allen, VA 23060 sales@searchblox.com | (866) 933-3626
Still learning about AI? See our comprehensive Enterprise Search RAG 101 and ChatBot 101 guides.
©2024 SearchBlox Software, Inc. All rights reserved.