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Development tool for GenAI adoption
![Enhancing User Experience with Responsive Technology A close-up of a hand interacting with a laptop touchscreen in a dimly lit environment, representing seamless user experience and digital responsiveness.](/.imaging/focalpoint/1600x960/dam/jcr:d22e975b-bcaf-40fe-be09-8bdd2c8028c7/gft-image-news-rag-assistant.webp)
RAG Assistant transforms AI and data projects
Pre-built frameworks eliminate inefficiencies, allowing businesses to launch projects faster with proven, curated tools.
Decision-makers benefit from clear performance metrics, optimized cost structures, and reduced latency, ensuring reliable and cost-effective Generative AI solutions.
3 key features
RAG prototype builder
Quick prototype builder with lots of options of LLMs, RAG types and more. This feature allows you to quickly build a Q&A bot in seconds, enabling full configuration of every aspect of the system.
![Create New RAG Scenario Create New Scenario interface for OpenData_Assistant with file upload option for customization](/.imaging/focalpoint/1600x900/dam/jcr:ff5bea8d-2f05-4c66-b96e-93703f4116e2/07_RAG-Assistent_01.webp)
![Monitoring RAG Assistant Performance - OpenData Assistant Insights Screenshot of the Monitoring Assistant interface displaying historical data for OpenData_Assistant, showing queries and evaluation scores on open data-related responses](/.imaging/focalpoint/1600x900/dam/jcr:f6482450-0506-4587-bf19-d5f115dcb006/07_RAG-Assistent_03.webp)
RAG evaluator
Semi-automatic evaluation of prototypes in terms of accuracy, cost and latency. A set of functionalities to evaluate results using test cases in a semi-automatic way.
Guardrails & User feedback
The system analyses every user input and system output, assessing ethical considerations, PII content, and sentiment. Additionally, it supports user acceptance testing (UAT) processes by providing feedback capture elements.
![User Feedback Interface for RAG Assistant Response Evaluation Screenshot of the response evaluation window where users can rate and provide feedback on the RAG assistant's performance in real-time, improving its efficiency and accuracy](/.imaging/focalpoint/1600x900/dam/jcr:84261b54-01c5-4328-843f-2eb2ce2e93c0/07_RAG-Assistent_04.webp)