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Architecure LynxAcribe Mob-3
The Architecture
  • Gen AI Applications Layer

     

    The Gen AI applications layer offers ready-to-use solutions for the most common use cases that can be addressed by LLMs. Unlock the power of interactive dashboarding with real-time analysis, leverage chatbots for exceptional customer service and sales, or streamline your campaign and content management with automated processes.

    LynxScribe - New Architecture 1

     
     

     

  • Application Enablers

     

    The application enablers layer lets you gain full control over LLMs and other foundational models. Our aim is to minimize the impact of hallucinations and incorrect answers, ensuring the highest level of accuracy. This layer seamlessly supports both the application layer and any custom applications through a Python API. 

    aak

     

  • LLM Handlers Layer

     

    The LLM Handlers layer includes comprehensive handlers for major LLM API providers such as OpenAI, Azure Open AI Studio, NVIDIA's NeMo, Vertex AI (PaLM), Hugging Face, and more. This allows you to select the best Generative AI solutions tailored to your specific needs.

    handle

     

  • Data & Modeling Layer

     

    Data & Modeling layer offers a range of benefits. Firstly, it enables you to create a knowledge graph or knowledge base by leveraging your existing structured and unstructured data sources. Furthermore, it collects logs generated by the application, providing valuable insights for fine-tuning every aspect of the platform. Additionally, you have the option to store your existing models within this layer, which can be utilized by applications supporting inbound sales or campaigns.

    Data

     

  • Gen AI Applications Layer
  • Application Enablers
  • LLM Handlers Layer
  • Data & Modeling Layer

Gen AI Applications Layer

 

The Gen AI applications layer offers ready-to-use solutions for the most common use cases that can be addressed by LLMs. Unlock the power of interactive dashboarding with real-time analysis, leverage chatbots for exceptional customer service and sales, or streamline your campaign and content management with automated processes.

LynxScribe - New Architecture 1

 
 

 

Application Enablers

 

The application enablers layer lets you gain full control over LLMs and other foundational models. Our aim is to minimize the impact of hallucinations and incorrect answers, ensuring the highest level of accuracy. This layer seamlessly supports both the application layer and any custom applications through a Python API. 

aak

 

LLM Handlers Layer

 

The LLM Handlers layer includes comprehensive handlers for major LLM API providers such as OpenAI, Azure Open AI Studio, NVIDIA's NeMo, Vertex AI (PaLM), Hugging Face, and more. This allows you to select the best Generative AI solutions tailored to your specific needs.

handle

 

Data & Modeling Layer

 

Data & Modeling layer offers a range of benefits. Firstly, it enables you to create a knowledge graph or knowledge base by leveraging your existing structured and unstructured data sources. Furthermore, it collects logs generated by the application, providing valuable insights for fine-tuning every aspect of the platform. Additionally, you have the option to store your existing models within this layer, which can be utilized by applications supporting inbound sales or campaigns.

Data

 

Some Use-Cases for our Generative AI Platform

Expert assistant for customer service

Provides fact-checked responses from compliance-vetted knowledge bases, with business rules acting as guardrails

Screenshot 2023-09-04 at 9.09.28 AM

Self-serve analytics and dashboards 

Users can use natural language to interrogate enterprise data and generate visualizations  

CHI with Assistant (1)

Personalization engines & content suggestions

Users are presented with personalized messages and content based on profile information, interaction history, etc. without the need to create business rules and content catalogs 

Screenshot 2023-09-04 at 2.05.40 PM

Python code generator with Copilot-type functionality

Developers get automatic code suggestions and can let the system complete low-level tasks

Python Example

Sentiment Analysis

Leverage Natural Language Processing (NLP) to gain insights about brand perception, customer satisfaction, product adoption & advocacy, etc.

Sentiment Analysis Example

The Lynx Difference

 

The extensive utilization of Graph AI and Knowledge Graphs in our platform enables the rigorous codification of specific knowledge, thus improving  the performance of any LLM for knowledge-intensive and domain-specific tasks. This approach offers several benefits: 

Create Generative AI applications that can behave according to industry norms or a specific regulatory framework  
Achieve greater accuracy of results and the ability to test these results with a formal test framework developed by Lynx Analytics
Avoid hallucinations and catastrophic forgetting by ensuring LLM-based applications rely mostly on curated data with a known structure 
Support greater transparency and explainability of outputs, enhancing the trustworthiness and accountability of the system
Log conversations and visualize them to understand how the structure of a knowledge graph led to specific interactions between a user and an application 

 

Our Technology Partners

Logo Technologies - Mobile
 
We offer services to deploy our Generative AI platform in your current environment, help you develop applications, and put them into production. Having completed several Generative AI deployments of our technology for enterprise clients, we are in the best position to help you roll out Generative AI applications for your internal or external customers, and combine them with advanced analytics capabilities.