Curated

(5/5)

BambooHR AI-Powered Company Policies and Benefits Chatbot

STEP 1: Retrieve company policies and load them into a vector store

Integrations Used (17)

Documentdefaultdataloader

Embeddingsopenai

Textsplitterrecursivecharactertextsplitter

Outputparserautofixing

Outputparserstructured

Workflow Structure (39 nodes)

100%

Manual Trigger

When clicking ‘Test workflow’

Bamboo Hr

GET all files

Filter

Filter out files from undesired categories

Split Out

Split out individual files

Filter

Filter out non-pdf files

Bamboo Hr

Download file from BambooHR

Langchain.embeddings Open Ai

Embeddings OpenAI

Langchain.vector Store Supabase

Supabase Vector Store

Langchain.text Splitter Recursive Character Text Splitter

Recursive Character Text Splitter

Langchain.document Default Data Loader

Default Data Loader

Langchain.chat Trigger

Employee initiates a conversation

Langchain.lm Chat Open Ai

OpenAI Chat Model

Langchain.embeddings Open Ai

Embeddings OpenAI1

Langchain.vector Store Supabase

Supabase Vector Store Retrieval

Langchain.memory Buffer Window

Window Buffer Memory

Langchain.agent

HR AI Agent

Langchain.tool Vector Store

Vector Store Tool

Langchain.lm Chat Open Ai

OpenAI Chat Model1

Langchain.tool Workflow

Employee Lookup Tool

Execute Workflow Trigger

AI-Powered HR Benefits and Company Policies Chatbot

Langchain.text Classifier

Text Classifier

Langchain.lm Chat Open Ai

OpenAI Chat Model2

Bamboo Hr

GET all employees

Bamboo Hr

GET all employees (second path)

Filter

Filter out other employees

Aggregate

Extract departments

Set

Stringify employee record for response

Set

Ensure uniqueness in department list

Langchain.information Extractor

Extract department

Langchain.lm Chat Open Ai

OpenAI Chat Model3

Bamboo Hr

Retrieve all employees

Filter

Filter out other departments

Aggregate

Extract relevant employee fields

Langchain.lm Chat Open Ai

OpenAI Chat Model4

Langchain.lm Chat Open Ai

OpenAI Chat Model5

Langchain.chain Llm

Identify most senior employee

Langchain.output Parser Autofixing

Auto-fixing Output Parser

Langchain.output Parser Structured

Structured Output Parser

Set

Format name for response

Node Types:

trigger

default

logic

transform

Requires credentials

Prerequisites

Required Credentials (3)

Bamboo Hr

Used by: GET all files, Download file from BambooHR +3 more

Docs

OpenAI

Used by: Embeddings OpenAI, OpenAI Chat Model +6 more

Docs

Supabase

Used by: Supabase Vector Store, Supabase Vector Store Retrieval

Docs

Multiple services required

This workflow needs 3 different credentials. Make sure you have accounts for all services before importing.

Complexity

Advanced

Expert level. Custom code, complex logic, many integrations.

Setup time: ~50 min

Score: 65/100

Conditional Logic

5 Integrations

When to Use This Workflow

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

Time Savings

Replace repetitive manual tasks with reliable automation.

Reclaim hours every week for higher-value work.

Error Reduction

Eliminate human error from routine processes with consistent automation.

Improve accuracy and reliability across your workflows.

workflow.json

{
  "id": "dYjQS1bJmVSAxNnj",
  "meta": {
    "instanceId": "a9f3b18652ddc96459b459de4fa8fa33252fb820a9e5a1593074f3580352864a",
    "templateCredsSetupCompleted": true
  },
  "name": "BambooHR AI-Powered Company Policies and Benefits Chatbot",
  "tags": [],
  "nodes": [
    {
      "id": "832e4a1d-320f-4793-be3c-8829776a3ce6",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        760,
        560
      ],
      "parameters": {},
      "typeVersion": 1
    },
...