Retrieval-Augmented Generation (RAG)

Transform AI with Teneo and RAG

Create accurate, effective, and cost-optimized LLMs with Teneo RAG, which solves the lack of visibility, monitoring, control, and insights for live RAG deployments built in AI Studio, PromptFlow, or LangChain.

Teneo Rag in Action

Teneo RAG in Action

Discover How AI is Revolutionizing Airline Customer Service

6 Challenges with RAG

While RAG offers promising AI capabilities, transitioning from a proof of concept (POC) to a live environment presents challenges:


Monitoring and Control

Effective monitoring and control mechanisms are essential to manage RAG's output, a key challenge in maintaining consistent quality in live scenarios. 


Limited Visibility and User Feedback Integration

The lack the capability to fully see and understand user interactions, hindering the ability to control responses and integrate user feedback effectively. 

rag challenges without teneo

Maintaining Relevance and Accuracy

Continuous updates and maintenance are necessary for RAG to stay relevant and accurate, a task that grows increasingly complex in live environments. 


Complex Integration

Integrating RAG into existing systems comes with high cost of technical labour and often becomes a hurdle in moving from POC to full-scale deployment. 

rag challenges without teneo

Scalability Issues

Scaling RAG from a controlled POC environment to handle diverse, real-world data and interactions is challenging in performance and reliability. 


Performance Optimization

Ensuring RAG operates with optimal speed and accuracy across various business scenarios is a significant challenge during the scaling process. 

Introducing Teneo Copilot

Teneo Copilot allows you to use any LLM to generate entries into your Teneo solution. Effortlessly create new entries and responses using Copilot's user-friendly interface, speeding up your workflow and enhancing your development skills. 

Generate Classes

Generate Responses

Create Entities

Add Your Own LLM

GIF showing how to generate Example Training data and Example Test data based on a description in Teneo.

Why Teneo for RAG 

With Teneo RAG your LLM will be accurate, effective and cost optimized. 

Discover how Teneo makes RAG more efficient, reliable, and insightful for your business needs:  

RAG - Generative AI cost reduction

98% Cost Reduction

Teneo´s RAG is based on FrugalGPT and increase accuracy with prompt tuning.

RAG - Generative AI cost reduction

Monitor RAG Behavior

Teneo's monitoring tools allow businesses to understand and validate RAG's responses, ensuring AI interactions are aligned with business goals.

Monitor RAG Behaviour

Control AI Responses

Adjust and refine RAG's outputs with Teneo's control features, ensuring accuracy and relevance in every interaction. Teneo cover the areas that RAG misses.

Control AI Responses in RAG

Listening to User Interactions

Teneo analyzes user interactions with RAG, providing insights to tailor AI responses to your audience's needs. Teneo defines which flow to call, extract info and orchestrates.

Listening to User Interactions

Benefits of Teneo RAG

Teneo enhances RAG's efficiency, ensuring faster and more effective AI operations.

Gain deep insights into user preferences and behavior with Teneo's advanced analytics.

Customize RAG's functionalities to suit specific business requirements and scenarios with Teneo's flexible tools.

Get Started with RAG

See Teneo + RAG in action by siging up for a FREE Trial now.