Retrieval Augmented Generation (RAG) LLM Chatbot

Sebastiaan Wiechers

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Prompt Engineer

Cloud Infrastructure Architect

Frontend Engineer

HubSpot

Next.js

Development of a custom chatbot and up-to-date data ingestion pipeline, taking and storing data points in a vector database, that can be retrieved in real-time through a user-facing chatbot.
Grounding LLM calls in real-world data is the best way to prevent hallucinations, and serve your customers or employees with an easy and accessible way to interact with the data that you want.
We use AI to suggest custom messages for clients in our CRM, which saves our sales team time during outreach campaigns.
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Posted Mar 21, 2024

Developed a LLM chatbot using Retrieval Augmented Generation to ground outputs on CRM data and company documents.

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Prompt Engineer

Cloud Infrastructure Architect

Frontend Engineer

HubSpot

Next.js

Development of an AI-powered product configurator
Development of an AI-powered product configurator
Development of a custom ETL solution
Development of a custom ETL solution