How I Built A Hazard Reporting AI Chatbot.

How I Built A Hazard Reporting AI Chatbot.

May 6, 2024
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Author: Nick Ning

Building an Instant Reporting Chatbot with GPT-4 Vision and Voice Flow

Are you looking for a way to streamline your reporting process and improve safety in your workplace? Look no further than an instant reporting chatbot that uses GPT-4 Vision and Voice Flow. With this chatbot, you can upload images of potential hazards and use GPT-4 Vision to identify the hazard, its severity, likelihood, and risk. You can also query an Airtable database full of job sites to find the right job site that the user has specified. Dynamic buttons showcase all of the potential staff members at that job site at the time, so they can select if anybody was injured using a multi-select tool. All of this data is captured and stored in an Airtable database for easy access and analysis.

Uploading Images of Potential Hazards

To get started with the instant reporting chatbot, the user will need to upload an image of the potential hazard. This is done using Voice Flow's file upload block, which is included in the VG template download from voice.org. Once the image is uploaded, GPT-4 Vision is used to identify the hazard and provide an immediate action that needs to be taken to control the situation and mitigate danger.

Identifying the Hazard, Severity, Likelihood, and Risk

After the hazard is identified, the chatbot will prompt the user to identify the severity, likelihood, and risk of the hazard. This is done using prompts that ask the user to output one word that describes the severity, likelihood, and risk of the hazard. The severity and likelihood are compared to a risk hazard matrix, which is also identified using GPT-4 Vision.

Finding the Right Job Site and Identifying Injured Workers

Once the hazard is identified and its severity, likelihood, and risk are determined, the chatbot will query an Airtable database full of job sites to find the right job site that the user has specified. The chatbot will then prompt the user to identify if anyone has been injured. If someone has been injured, the chatbot will use the job site data to pull all of the staff members at that job site and generate a carousel of dynamic buttons using Voice Flow's AI prompt.

Storing Data in an Airtable Database

All of the data captured by the chatbot is stored in an Airtable database for easy access and analysis. The chatbot will send all of the data through to make.com, which will process the data and upload it directly into the job site database.

Pros and Cons

Pros:

- Streamlines reporting process

- Improves safety in the workplace

- Easy access and analysis of data

Cons:

- Requires some technical knowledge to set up

- May not be suitable for all workplaces

Highlights

- Instant reporting chatbot that uses GPT-4 Vision and Voice Flow

- Upload images of potential hazards and identify the hazard, its severity, likelihood, and risk

- Query an Airtable database full of job sites to find the right job site that the user has specified

- Generate a carousel of dynamic buttons using Voice Flow's AI prompt

- Store all data in an Airtable database for easy access and analysis

FAQ

Q: What is GPT-4 Vision?

A: GPT-4 Vision is a machine learning model that can identify objects and scenes in images.

Q: What is Voice Flow?

A: Voice Flow is a platform for building conversational AI experiences.

Q: Can this chatbot be customized for my business?

A: Yes, you can book a call through the author's calendar link in the description to discuss your project and work on building out a custom chatbot for your business.

Resources:

- [Voice Flow](https://www.voiceflow.com/)

- [Airtable](https://airtable.com/)

- [Make.com](https://www.make.com/)

- [GPT-4 Vision](https://openai.com/blog/dall-e-2-and-gpt-4/)

🤖 Introducing VOC.AI's AI Chatbot: https://www.voc.ai/product/ai-chatbot. This AI chatbot can automatically reduce large amounts of work on customer services.

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