AI

Travel Insights Assistant

Student final project · Agentic AI course

A small AI travel research system built as one connected workflow.

This project combines guided input, workflow automation, content collection, API testing, structured storage, and dashboard update in one practical system.

Hugging Face Typebot n8n Airtable Postman Firecrawl

Input

Guide travel requests in a clear format

Collect

Gather insight data from web sources

Store

Keep results in structured Airtable records

Update

Refresh the final dashboard output

Goal: create one simple system for travel insight collection and delivery, not only a chatbot screen.

Typebot flow

Structured prompts first.

I built a guided chat flow to collect user requests.

This makes prompts cleaner before automation starts.

Tech stack: Typebot + prompt flow design.

n8n pipeline

From input to action.

This workflow receives data from Typebot.

It moves the project from chat to backend logic.

Tech stack: n8n + webhook + routing steps.

Firecrawl test

Test before integration.

I tested Firecrawl in Postman first.

This confirmed that article text was returned correctly.

Tech stack: Postman + Firecrawl API.

Data collector

Collect and prepare data.

This workflow gathers and processes insight content.

It replaces slow manual collection.

Tech stack: n8n + workflow automation.

Airtable records

Structured storage.

I stored title, source, summary, and URL as records.

This gives the project a simple database layer.

Tech stack: Airtable + field mapping.

Airtable test

Read records by API.

I tested Airtable retrieval in Postman.

This proved the records could be read in JSON.

Tech stack: Postman + Airtable API.

HF updater

Push data to output.

This step sends prepared data to the final app layer.

It connects stored records with visible output.

Tech stack: n8n + Hugging Face update flow.

These screens show the dashboard before and after the update.

They make the full workflow visible from input to final result.

System summary

One project, many connected tools.

This case study shows workflow thinking, API testing, structured storage, and practical AI automation for travel-related research.

Input Automation Validation Storage Update Output