Artificial Intelligence for Real Estate

How to Integrate ChatGPT into Real Estate

Estimated read time: 17 minutes

If you are reading this page, you want to know how to utilize ChatGPT for a real estate business. To integrate ChatGPT into any real estate business application, you need to plan, prepare, and execute a complex software development project. Read on as we will cover the steps you need to follow in this guide.

1. Assemble an expert team to kick-start a project to utilize ChatGPT for real estate apps  

You could conceivably have a strategic, large, and complex project to integrate ChatGPT into a real estate industry application. ChatGPT, a famous LLM (Large Language Model) utilizes specialized Artificial Intelligence (AI) technologies. You need the right experts to kick-start a real estate ChatGPT project on the right note.

You might need this expert team to do the following:

  • They should consider what ChatGPT for real estate applications can achieve for you.
  • Experts need to analyze risks and determine whether a real estate ChatGPT integration project makes sense for you. 
  • Defining the project, requirements, and technical solutions definition is a critical task.
  • You need this team to identify the right ChatGPT integration approach.
  • This expert team should plan the project.

Assemble this team by onboarding the following participants:

  • A project manager (PM): Assisted by deep knowledge of project management methodologies, the PM should lead the team and prepare a comprehensive project plan. 
  • An architect: By utilizing technical as well as real estate market expertise, the architect should define the technical solutions. You need the architect to define the non-functional requirements (NFRs) too.
  • A business analyst (BA): The BA needs sound knowledge of the real estate business today. Expect the BA to elicit business requirements from the real estate professionals in your organization. The BA should gather, analyze, and document the functional requirements

2. Decide whether you should integrate into a real estate business application 

Should you integrate ChatGPT into your real estate website and mobile application at all? Your answer should depend on the values that Chat GPT can deliver and the associated risks. The PM and architect should analyze them.

What can you gain by integrating ChatGPT into your real estate industry app?

You might get the following advantages out of this popular AI technology solution:

  • ChatGPT can provide human-like responses to the standard questions from current and potential clients. This can save time considerably for your customer support team. 
  • Since ChatGPT is available 24×7, you can enhance your round-the-clock customer support operations with the help of ChatGPT-powered AI bots.
  • A ChatGPT-powered chatbot can answer many questions simultaneously from potential sellers and buyers. You can scale your customer support operations better.
  • You can use this powerful tool to intelligently automate repetitive tasks that are time-consuming.
  • Businesses can use ChatGPT for content creation.
  • If you serve multiple geographies with different languages, then you can use the multilingual support provided by ChatGPT to great effect.

What risks do you need to contend for integrating ChatGPT into your app?

The risks of ChatGPT integration and the corresponding mitigation measures are as follows:

  • ChatGPT doesn’t always provide accurate responses. You might have dissatisfied customers in that case. You can mitigate this risk by training ChatGPT for real estate using your own data sets. 
  • Search engines like Google view AI-generated content negatively. SEO (Search Engine Optimization) score of your company’s blog posts can take a beating. Naturally, you will see a cascading and negative impact on your social media marketing and other digital marketing initiatives. Mitigate this risk by implementing rigorous policies and procedures by writing and publishing website content. Prevent your team from using AI content as-is while writing app content, marketing content, etc. 
  • ChatGPT might not provide effective solutions and valuable insights to your customers. Once again, the only mitigation measure for this is to train ChatGPT with your own data sets.
  • You might need to spend considerable time and effort to integrate ChatGPT into your apps. If you need to train ChatGPT with your own data, then the complexity increases manifold. While a strategic project will require sufficient time, you can mitigate this risk by implementing the right project management and software development processes.
  • ChatGPT requires plenty of computing resources, which might act as a bottleneck. To mitigate this risk, plan the IT infrastructure of your project early enough and use cloud platforms like AWS or Azure when needed.

So, do you see more advantages of using ChatGPT? Or, do the risks outweigh the advantages? Analyze these and make the decision. 

3. Define the project scope and requirements

Assuming you have decided to integrate ChatGPT into your real estate applications, take the next steps now:

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3A. Elicit business requirements from stakeholders like real estate agents and finalize requirements

The BA in your team needs to meet the business stakeholders in your organization. These meetings should result in a list of “needs” from the business stakeholders.

The BA should analyze these and refine them as business requirements. Subsequently, the BA should write up the requirements. The following are examples of what you could cover in requirements:

  • Generating social media posts using ChatGPT;
  • Writing property descriptions with the help of ChatGPT;
  • Getting insights from local market trends using ChatGPT;
  • Drafting legal documents and video scripts with the help of ChatGPT;
  • Utilizing ChatGPT to write listing descriptions and property details
  • Generating ideas using ChatGPT for the next marketing campaign;
  • Using ChatGPT to generate content for virtual tours of properties;
  • Expediting the writing of property listings using AI-generated text produced by ChatGPT;
  • Writing phone scripts using ChatGPT.

3B. Write up the technical requirements

The architect should analyze industry benchmarks and document the non-functional requirements, i.e., technical requirements. A few examples of such requirements are as follows:

  • Performance;
  • Scalability;
  • Maintainability;
  • Usability;
  • Testability.

3C. Define the project scope

We assume that you already have web and/or mobile apps for your real estate business. Therefore, you will integrate ChatGPT into these websites/mobile apps. Define the project scope, e.g.:

  • You need to create an AI chatbot.
  • Train ChatGPT with your own data only if requirements demand that.
  • Integrate ChatGPT into your chatbot.
  • You need to integrate the chatbot into your mobile and web apps.

3D. Implement the right requirements management processes

You need the PM to select, implement, and fine-tune the appropriate requirements management processes. The PM needs to ensure the following:

  • Your team should follow the relevant standards and best practices to write project specifications.
  • A qualified reviewer should review the specifications.
  • The appropriate stakeholders should approve the requirements.
  • The PM needs to implement a robust requirements change management process.

4. Select a ChatGPT integration approach

You now have finalized the business requirements, therefore, you can choose the right ChatGPT integration approach. We assume that you have several complex and customized requirements and not very straightforward ones. 

You should develop a custom AI chatbot after training ChatGPT in-house with your own data. This approach involves the following steps:

  • Download the ChatGPT LLM and host it using a suitable cloud hosting provider.
  • Train ChatGPT yourself with data sets from your business.
  • Develop an AI chatbot from scratch.
  • Integrate the ChatGPT model trained by your team into the new chatbot.
  • Integrate the chatbot into your web and mobile apps.

This approach delivers the maximum value to your real estate organization and real estate agents. Since it’s a complex approach, you need highly competent AI developers. They should know ChatGPT and chatbot development very well. 

ChatGPT integration approaches with fewer or no customization options

The following are just a few ways to integrate ChatGPT, however, these approaches offer limited or no customization options:

  1. You can use a chatbot builder platform to build a chatbot and train ChatGPT with your own data. These platforms are typically no-code or low-code platforms. You can manage this with a mid-level developer, however, the customization options depend on the chatbot builder.
  2. Build a chatbot using a no-code chatbot builder platform like Chatfuel without training ChatGPT with your data. Even a junior developer can do this, however, you get even fewer customization options.
  3. You can integrate only the ChatGPT API into your existing chatbot or website. While you can manage this with only junior developers, you get no customization options. 

5. Create technical solutions and the project plan

Based on the requirements and ChatGPT integration approach, the architect should create the technical solutions for this project. The technical solutions should cover all the key aspects, e.g.:

  • Technology stack;
  • Software development and testing tools to be used;
  • An estimate for the development and testing efforts;
  • Internal and external dependencies;
  • Human resource requirements, e.g., skill requirements;
  • Technical delivery-related risks.

The PM should create a comprehensive project plan covering all key areas, e.g.:

  • Project’s technical environment;
  • Project schedule;
  • Cost estimate;
  • Project management methodologies and frameworks to be used;
  • Important project management knowledge areas like human resource management, communications management, etc.

6. Hire developers to integrate ChatGPT into your real estate app

We assume you chose to integrate ChatGPT into a new chatbot, and you will train the LLM with your data in-house. You need to hire AI/ML/NLP (Natural Language Processing) developers with the following skills and experience:

  • Python;
  • Chatbot development experience;
  • Knowledge in LLMs like ChatGPT;
  • Experience with training LLMs and AI/ML models.

You also need to hire testers and DevOps engineers.

Do the following:

6A. Decide on the appropriate hiring platform

You can hire developers from freelance platforms or a reputed software development company like DevTeam.Space. Some businesses toy with the idea of hiring freelancers. You should know the risks associated with it, which are as follows:

  • You might not get competent developers since it’s hard to evaluate the real experience of freelancers.
  • Freelancers might not work with enough focus on your project. They often work simultaneously for multiple clients.
  • You might find it hard to manage the work of freelancers due to time-zone differences. Freelance platforms don’t offer any project management support.
  • Freelancers might leave your project mid-way. You will face project delays, and you need to hire replacement developers.

Your strategic project might get derailed due to these risks, which you can ill afford!

Hire from a trustworthy software development partner like DevTeam.Space. We offer the following advantages:

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  • Our vetting processes ensure that our developers have the relevant expertise and extensive experience.
  • We offer all round professional development opportunities, therefore, our developers are motivated.
  • Our developers work full-time on your project.
  • We train them in our world-class development processes, which help them succeed in complex projects.
  • Our AI-powered agile processes ensure transparency and efficiency.
  • You always get supportable and maintainable code from us, thanks to our focus on quality.
  • You get complimentary support from a dedicated tech account manager, who helps with project management.

6B. Interview developers

Having chosen a hiring platform, you now need to interview the candidates. If you hire AI developers from DevTeam.Space, then you can take interviews quickly. We have stringent vetting processes, therefore, you can rest assured about the quality of developers. 

However, you need to take a very detailed interview if you hire freelancers. You should cover all the relevant technologies in detail. 

You can use interview questions found on the Internet. Our Python interview questions and SQL interview questions are good examples.

Your questions must aim to find the relevant experience of developers and not remain confined to theory. Therefore, you should ask how developers solved past project problems. 

You also need to know whether the candidates worked on projects like yours. Explain your project. Hear from them about the approach they would take for such a project. 

You should only hire developers who provide honest, straightforward, and specific answers. Avoid hiring candidates who use jargon. 

6C. Onboard the developers you hired

You hired developers, and now you want them to be productive as soon as possible. The PM leading your software development team should onboard the new developers effectively. An effective onboarding should include the following:

  • A thorough orientation program: It should cover the values, policies, and processes in your organization. You need to cover regulatory requirements concerning data security and privacy. 
  • An overview of the project: The PM and architect should explain the requirements and technical solutions.
  • Access: New developers should get access to the project’s technical environment promptly.
  • An explanation of the project plan and schedule: The PM needs to explain the project plan, timelines, and iterations. This explanation needs to include the software development processes followed in the project.
  • The team: You need to introduce the new team members to the existing team. Set up a communication process. 

7. Execute and control the ChatGPT integration project into your real estate industry app

You are now at the business end, therefore, do the following:

7A. Train ChatGPT with your data

You need to approach the complex task of training ChatGPT with your own data carefully. Do the following:

7A.1. Collect the relevant data

You need to collect the relevant data for training ChatGPT. Data could come from varied sources. You might have different types of data, e.g.:

  • Social media posts published by your marketing team;
  • Marketing materials built by the marketing team;
  • Property descriptions;
  • Knowledge assets created by real estate agents;
  • Commercial property listing descriptions;
  • Video and call scripts;
  • Social media marketing assets;
  • Legal documents;
  • Questions asked by clients about automated valuation models;
  • Market reports;
  • Analysis and reports on mortgage payments.

Organize data after collecting them.

7A.2. Clean and preprocess data

You need to clean and process data since you can’t use raw data for training the ChatGPT LLM or any AI/ML model. 

First, analyze data sets, which involves the following:

  • Your team needs to identify trends and patterns in the data sets.
  • The team must examine the data sets for outliers.
  • Team members need to pinpoint different exceptions in the data.
  • You need to identify inconsistencies and biases in the data sets.

Second, your team needs to organize data in an appropriate format. This helps you achieve consistency. You might need different approaches depending on the data sets, e.g., standardizing values in a few columns.

As the third step, you must improve the quality of the data. This task can take time due to the following reasons:

  • Your team might need to enter missing values.
  • Extreme values might need standardization.
  • You need to deal with outliers in the data sets.
  • The team might need to correct discrepancies in data.

Use the right data preparation tools for this crucial step.

Fourth, you need to split the data sets for training and testing the LLM. Your team must arrive at the right split after careful analysis.

Finally, keep all of the data sets handy. You will need to feed them to “training” script later. 

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7A.3. Set up the environment to train ChatGPT

You now need to establish the environment to train ChatGPT with your data. This important step involves the following steps:

You need to create an OpenAI account and get an API key for the ChatGPT API. Secure the API key carefully.

Your team now needs to set up a large enough server for self-hosting the ChatGPT LLM. We recommend you use a reputed cloud provider like AWS or Azure for this.

The team needs to install Python by following the relevant instructions. Developers need to upgrade Pip, the Python package manager. 

It’s time to install the following dependencies now:

  • Your team needs to install the OpenAI library. 
  • This project also needs GPT Index since you need to connect the ChatGPT LLM to your knowledge base. 
  • Install PyPDF2, a useful tool for parsing PDF files. 
  • You also need the PyCryptodome library, the Python library to secure your data. 
  • Install the Gradio library, which helps you create a user interface to interact with ChatGPT.

The AI developers in your team need to create the Python scripts for training the LLM with your data. Developers should reference your secret OpenAI API key in the script. 

7A.4. Train the self-hosted LLM  

Your team should now create one folder and add all of the training data sets into it. The team needs to execute the Python script for training against that folder. 

Evaluate the performance of the trained model. If needed, your team needs to improve the data quality and train the model again.

7B. Develop the chatbot, integrate ChatGPT, and integrate the chatbot into your apps

You now have the self-hosted version of ChatGPT LLM trained with your data. Your team needs to take the following steps now:

  • The team needs to design the user interface (UI) of the proposed chatbot.
  • Chatbot developers need to code the chatbot using Python.
  • The next step involves integrating the self-hosted LLM into the chatbot.
  • Your team needs to test the chatbot.
  • Subsequently, the team needs to integrate the chatbot into your web and mobile apps.

The PM needs to monitor and control the project execution using the right tools and processes.

Submit a Project With Zero Risk

Due to its strategic nature, you could find a real estate ChatGPT integration project a large and high-visibility one. Artificial Intelligence and its various branches like Natural Language Processing (NLP) are niche technologies. You often find projects involving such technologies to be complex. 

Right planning and execution hold the key to your success. You need top-notch developers with extensive knowledge of different AI technologies, AI tools, and AI models. Also, you will likely need highly competent web and mobile developers. 

The good news is that we at DevTeam.Space have developers with relevant expertise. Our developers go through a stringent vetting process. They have in-depth skills and extensive experience. Our human resource management practices ensure that they have high motivation levels. We train our developers in our AI-powered agile process.

Do you want to know more about how we can help? Fill out the DevTeam.Space product specification form and a dedicated tech account manager will soon reach out to you. 

FAQs

1. Can DevTeam.Space guide me with the steps to secure sensitive information when I train ChatGPT with my own organization’s data?

DevTeam.Space has extensive expertise both with training ChatGPT and data security solutions in the software development industry. We can certainly support your request. You will need to take several important steps, e.g.:
Anonymizing and removing PII (Personally Identifiable Information) and other sensitive data;
Implementing stringent technical and physical security controls;
Keenly guarding against application security vulnerabilities;
Routinely monitoring information security policies, controls, technical measures, and practices in your organization.
We believe that a complimentary discovery call between you and a dedicated tech account manager from our team will help. Please submit the DevTeam.Space product specifications form for this.

2. Can DevTeam.Space experts guide me with the steps for cleaning and preprocessing my own data sets for training ChatGPT?

DevTeam.Space teams have in-depth expertise in training AI/ML models including LLMs like ChatGPT with custom data, and we can certainly help you. The cleaning and preprocessing of data might involve several steps, and the following are just a few examples:
Correcting formatting issues in data sets;
Removing special characters and HTML tags from data;
Tokenizing the data, i.e., dividing the text into word or sub-word units;
Bringing in consistency in text by converting them into lowercase;
Eliminating stopwords like “is”, “the”, “and”, etc. from the text;
Removing meaningless and extra blank spaces between words.
We request a discovery call with you and your team to understand your requirements better. Note that it’s a complimentary call. 

3. If I don’t want to spend the large effort of training ChatGPT entirely on my own, what other options do I have?

You can use solutions like Botsonic and LiveChatAI, which are no-code platforms for building AI chatbots. These platforms handle the bulk of the workload involved in training ChatGPT with custom data. However, your customization options will depend on what the no-code platform provides, and you might get only limited elbow room.


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