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AI HubSpot Contact Manager

This AI-powered workflow automates contact management in HubSpot CRM. Users can easily search, create, or update contacts through a chat interface powered by an AI agent that leverages HubSpot tools and OpenAI LLM for intelligent interaction. Ideal for sales and RevOps teams seeking streamlined CRM operations.

How the AI Flow works - AI HubSpot Contact Manager

Flows

How the AI Flow works

User Initiates Contact Management.: The user opens the chat interface and is greeted with a welcome message and options to search, create, or update contacts.
User Selects or Enters Action.: Interactive buttons and chat input allow the user to choose whether to search for a contact, create a new one, or update existing details.
AI Agent Handles User Request.: An AI agent, powered by OpenAI and equipped with HubSpot tools, interprets user intent and determines the required CRM action.
HubSpot Contact Actions.: The workflow performs the required HubSpot operation: searching, creating, or updating a contact, based on the user’s input.
Display Results and Follow-Up.: Results are shown to the user in chat, and the agent may ask for additional information or confirm next steps to keep CRM data up to date.

Prompts used in this flow

AI Agent

AI Agent for managing contacts in HubSpot using tools and LLM. Contains user-provided backstory and goal as prompts for the LLM to guide agent's behavior.

Backstory:
Hubspot assistant

Goal:
you are a helpful AI assistant in charge of adding and updating contacts on Hubspot by using the Hubspot tools at your disposal always use the tools to do this.
you should gather the necessary information from the user and take necessary action (create or update that contact).

If a contact already exists let the user know and ask them if they want to update it or add a new contact.

and if user is searching for a contact search for it and give them a detailed answer

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

See Chat Output

Message Widget

The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.

See Message Widget

Button Widget

The Button Widget component in FlowHunt transforms text or input into interactive, clickable buttons within your workflow. Perfect for creating dynamic user interfaces, collecting user choices, and improving engagement in AI-driven chatbots or automated processes.

See Button Widget

Chat Opened Trigger

The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.

See Chat Opened Trigger

Chat History Component

The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.

See Chat History Component

LLM OpenAI

FlowHunt supports dozens of text generation models, including models by OpenAI. Here's how to use ChatGPT in your AI tools and chatbots.

AI Agent

The AI Agent component in FlowHunt empowers your workflows with autonomous decision-making and tool-using capabilities. It leverages large language models and connects to various tools to solve tasks, follow goals, and provide intelligent responses. Ideal for building advanced automations and interactive AI solutions.

Create a Contact in HubSpot

Automate your HubSpot CRM. Automatically find and create new HubSpot contacts from various sources, including internal docs and websites.

See Create a Contact in HubSpot

Update a Contact in HubSpot

Automate your HubSpot CRM. Automatically find and edit HubSpot contacts based on various sources, including internal docs and websites.

See Update a Contact in HubSpot

Search Contact in HubSpot

Build tools that automatically search and filter HubSpot contacts using virtually any property, both standard and custom.

See Search Contact in HubSpot

Flow description

Purpose and benefits

This workflow is designed to automate and streamline the process of managing contacts in HubSpot CRM. It provides an interactive chat-based assistant that can help users create, update, and search for contacts, ensuring that the contact list remains clean and up to date. The workflow leverages AI capabilities (OpenAI LLM) and integrates directly with HubSpot’s API, making it a powerful tool for scaling customer relationship management without manual intervention.

Workflow Overview

When a user opens the chat, they are greeted with a friendly welcome message outlining the assistant’s capabilities. The interface then offers actionable buttons for common tasks: searching for an existing contact, creating a new contact, or updating an existing contact. Based on the user’s selection or input, the workflow guides them through the required steps, collects necessary information, and interacts directly with HubSpot to execute the desired operation.

Main Components

Component	Functionality
Chat Opened Trigger	Detects when a user opens the chat and initiates the workflow
Message Widget	Displays a customizable welcome/instruction message
Button Widgets	Presents user with options: “Search for contact”, “Create new contact”, “Update contact”
Chat Output	Shows messages and responses to the user
Chat Input	Collects user input for free-form tasks and data entry
Chat History	Maintains a record of recent chat messages for context-aware responses
OpenAI LLM	Provides the AI assistant’s conversational and reasoning abilities
AI Agent	Orchestrates actions, calls tools, and generates responses
HubSpot Tools	Integrates with HubSpot API to create, update, or search for contacts

Step-by-Step Flow

Greeting and Options

When the chat is opened (ChatOpenedTrigger), the user is greeted with a welcome message via the MessageWidget.
The user sees clickable buttons for the main actions:
- Search for contact
- Create new contact
- Update contact

User Interaction

The user can click one of the buttons or type a message to specify their intent.
Depending on the button clicked, a corresponding message is displayed via ChatOutput nodes to confirm the action.

AI-Powered Assistant

The workflow maintains recent conversation context using ChatHistory (last 5 messages, up to 800 tokens).
It uses an OpenAI-powered LLM (OpenAILLM) as the backend for understanding user requests and generating intelligent, context-aware replies.
The AIAgent is configured with a clear goal and backstory: it is always to use HubSpot tools for contact management, gather necessary information, and decide the correct action (create, update, or inform about existing contacts).

HubSpot Integration

Three tool nodes interface with HubSpot:
- CreateContact: Adds a new contact using provided details.
- UpdateContact: Updates an existing contact based on provided information and contact ID.
- SearchContact: Looks up contacts by properties (e.g., email, name).
The AI agent uses these tools to perform the requested task, either by prompting the user for more details or by executing the operation directly.

Response and Output

After processing the request (create, update, or search), the AI agent communicates the results back to the user through the ChatOutput node, ensuring a seamless conversational experience.

Why is this Workflow Useful?

Automates Routine CRM Tasks: By facilitating contact management through natural language or button clicks, it removes repetitive manual data entry and lookup tasks.
Scalable Support: The AI agent can handle multiple concurrent requests, making it suitable for teams or customer support scenarios.
Consistency and Data Quality: The assistant always uses the correct process, ensuring that contacts are created, updated, or searched in a standardized way.
Context Awareness: With chat history and AI, the assistant can maintain context across multiple steps, making the conversation more natural and efficient.
User-Friendly: The combination of guided buttons and free-form chat input makes the experience accessible for users of all technical levels.

Example Use Cases

Sales Teams can quickly add or update contacts on the go, reducing administrative overhead.
Customer Support can look up or amend contact records during live conversations with customers.
Marketing Teams can ensure their lists are always up-to-date with minimal effort.

Summary Table

User Action	Outcome
Click “Search”	AI asks for search criteria, looks up contact, presents results
Click “Create”	AI collects info (name, email, etc.), creates contact in HubSpot
Click “Update”	AI asks for contact to update and new info, updates in HubSpot
Type a Message	AI interprets intent, asks clarifying questions, performs requested action

Automation & Scaling Benefits

Reduces manual errors and omissions
Frees up human resources for higher-value tasks
Enables 24/7 self-service for contact management
Provides a unified, intuitive interface for interacting with HubSpot

By leveraging this workflow, organizations can significantly enhance their CRM data hygiene, responsiveness, and operational efficiency.

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