Development tool for GenAI adoption

Developed by GFT Spain

07 October 2024

The Retrieval-Augmented Generation (RAG) Assistant is designed to reduce both the time to market and the overall cost of projects. It provides developers with a unified platform that covers quick prototyping, evaluation and also guardrails and UAT processes.

07 October 2024

A close-up of a hand interacting with a laptop touchscreen in a dimly lit environment, representing seamless user experience and digital responsiveness. — GFT focuses on enhancing user experiences through intuitive and responsive digital technologies. This image showcases the importance of interactive interfaces in delivering efficient, user-friendly solutions across various digital platforms.

GenAI adoption

RAG Assistant transforms AI and data projects

Reducing ROI uncertainty and delivering measurable results.

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.

How it works

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 Scenario interface for OpenData_Assistant with file upload option for customization

Screenshot of the Monitoring Assistant interface displaying historical data for OpenData_Assistant, showing queries and evaluation scores on open data-related responses

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.