How we built RAG Advise's AI platform for asking questions of company data

RAG Advise is a modern AI-driven platform designed to help teams unlock value from their internal data. By combining Retrieval-Augmented Generation (RAG) with structured data pipelines, the platform enables users to ask questions and receive reliable, context-aware responses.

AI · Enterprise knowledge platform
Ongoing partnership

Inside the build

Screens, flows and designs from the build.

5 images from the RAG Advise project. Select any image to see it larger.

RAG Advise assistant workspace with knowledge sources and channels on a laptop — **AI assistant workspace**Select an image to open the viewer, then use the arrow keys or swipe to move through all 5 images.

RAG Advise products and services catalog with the assistant panel on a laptop — **Products and services**Data is collected from multiple sources, cleaned, and structured to ensure consistency and accuracy before being prepared for intelligent querying.

RAG Advise weekly analytics view on a laptop — **Analytics**The processed data is indexed and connected with AI models, enabling real-time responses and insights through a conversational interface.

RAG Advise conversations inbox on a laptop — **Conversations**

RAG Advise assistant widget with quick actions on a laptop — **Assistant widget**

About the project

About RAG Advise.

RAG Advise is an AI-powered platform that enables businesses to interact with their data using natural language, delivering fast, accurate, and context-aware insights.

The system integrates multiple data sources into a unified interface, reducing dependency on manual searches and disconnected tools. It is built to support scalable workflows, improve decision-making, and enhance productivity across teams handling large volumes of information.

Client: RAG Advise
Industry: AI · Enterprise knowledge platform
Engagement: Ongoing partnership
Services: AI & Automation, RAG systems, Data integration, Product design

The challenge

Businesses often struggle with fragmented data spread across documents, CRMs, and internal systems. Finding accurate information quickly becomes time-consuming and inefficient.
Traditional search lacks context, while manual workflows lead to delays, errors, and poor visibility into data. Teams need a smarter way to access and utilize information without switching between multiple tools.

What we built

TechEsthete designed and developed an AI-powered platform that centralizes data and enables intelligent querying through natural language.

AI-Powered Search System: built a conversational interface that retrieves accurate answers from connected data sources.
Data Integration & Structuring: unified multiple data inputs into a clean, query-ready format for reliable AI responses.
User-Centric Interface Design: designed a modern and intuitive UI to simplify complex data interactions.
Scalable Architecture: developed a system capable of handling growing datasets and enterprise-level usage.

The result

Teams get faster, more accurate answers from their own data: less time spent searching across disconnected tools, and a foundation that scales as the underlying datasets grow.

What we worked on

What the build covered.

01AI & Automation
02RAG systems
03Data integration
04Product design

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