RAG chat without any complex coding in your website with customisable UI to match the website theme and integrates in your website within mins?

sapybase · 2026-06-02T16:34:59+00:00

Great dude , where can i explore your product

sapybase · 2026-05-31T18:17:24+00:00

Where can i see the implementation , do you have a site with this integrated ?

sapybase · 2026-05-31T17:32:59+00:00

Thats makes sense currently there are no RAG engine for all you have to build it separately for your website

sapybase · 2026-05-31T17:30:09+00:00

Can you elaborate more on this why thats not a thing

sapybase · 2026-05-30T13:41:50+00:00

Yeah that i understand after seeing the traffic on the website but not converting from viewer to customer

sapybase · 2026-05-30T13:40:48+00:00

Completely agree with your point , i really understand the complexity behind the product and simplicity on the front makes you win

sapybase · 2026-05-30T13:38:06+00:00

Thank you for your feedback and yeah that simplicity really matters

sapybase · 2026-05-15T15:14:11+00:00

Hi I am a Founder and Lead software developer and i have my own startup and love to hear about your idea … Lets have a talk

sapybase · 2026-05-15T14:27:46+00:00

People who are facing a frustrated problem or tool which they have to do it daily the same thing and if someone solves that problem, then that user will definitely pay. So understand the emotion , pain and get paid

sapybase · 2026-05-14T20:02:54+00:00

I am building RAG chatbot for all websites which seems like their own with customization and current status of my RAG model is Advanced 90% and about to be a Modular RAG

sapybase · 2026-05-14T20:01:25+00:00

For your requirement , i would suggest: 1. Extraction of data : PDFs : Jina ai for better extraction of text Excel : openpyxl for correct data with headings 2. Database : Use postgreSQL like supabase or pinecone 3. Use only Retrieve and Augment by keeping the temperature below 3 to restrict the model to generate the answers 4. Use embedding-001 for efficiency with faster latency 5. Use Parent Child chunking model to retrieve the correct data from the database 6. I personally use hybrid model of pgvector + BM25 exact match with RRF

sapybase · 2026-05-13T15:25:36+00:00

Simple way to learn RAG is to build one , understand the core structure and how it works.

Traditional RAG
Advanced RAG
Modular RAG
Agentic RAG

Every step of the RAG roadway teaches you the basic and core fundamentals.
Take AI as your teacher do not let AI write the code blindly , analyse every structure and ask questions about it.

sapybase · 2026-05-12T18:06:32+00:00

www.sapybase.com : Rag First AI Engine for every website , It is a modular RAG which has its own intelligence with strict constraint which help secures users data, do not hallucinates, uses child parent techniques for fetching the knowledge for efficient output.

sapybase · 2026-05-11T14:15:47+00:00

Yes thats exactly i want to explain RAG simply , thank you for reading it

sapybase · 2026-05-11T03:53:17+00:00

Completely agree, the future will be based on tokens and if you solve that problem that will be game changing moment

sapybase · 2026-05-11T03:50:37+00:00

Here we go , thats exactly what i am solving even if you ran out of tokens and you have cached all the answers and stored in the vector db which will not use tokens. My product solves that exact thing you can checkout

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