RAG (Retrieval Augmented Generation)

At Hoop Konsulting, we use Retrieval Augmented Generation (RAG) to deliver AI responses that are accurate, context aware, and grounded in your enterprise data ensuring reliability, compliance, and trust every time 

Products

Key Features

Project Journey

From Concept to Deployment: Our RAG Creation Process

Discovery & Strategy

01

Data Audit & Integration Setup

02

Indexing & Retrieval Design

03

AI Model Configuration

04

Prototyping & Testing

05

Deployment & Improvement

06

Foundation Models

GPT4, GPT Turbo

Claude

Gemini 1.5

Mistral

LLAMA 2&3

Langchain

Grok

Haystack

Pinecone

Cohere RAG

Weaviate

Command R

TTS & ASR

Eleven Labs

Vosk

Valle E

Amazon Polly

ConQuis TTS

Resemle AI

Whisper

Google STT

IBM Watson

Image, Audio, Video

Eleven Labs

Playground V2

Pika Lab

Synthesia

Suno AI

Sound Raw

Firefly AI

Runway AI

ADobe Premier

Da Vinci AI

Kaiber

Boomy

Multimodal Models

GPT Vision

Claude

Gemini 1.5

Grok

Clip AI

Kosmos -2

Object and Face Detection

Yolov 8

SAM.AI

Detectron

D-DI

Synthesia

Deepface

Heygem

Heygem

ZMO AI

Emotion Detection

Hume AI

Affectiva

Symanto

Watson Cone

Legal, Medical, Educational

Hume AI

Spell Book

Lunito

Lexion AI

Zebra Medical

Path AI

Khanmigo

Scribe AI

Socratic

Testimonials

What Our Clients Say

From startups to enterprises, our clients share how Hoop Konsulting delivered impact, value, and real results every step of the way.

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