CASE STUDY
Data Interactive Tool Powered by AI
New AI tools and developments emerge every day, which can be overwhelming. To help simplify things, we created a straightforward proof of concept to demonstrate practical ways businesses can implement AI.
CHALLENGE
Construction companies face challenges interpreting historical data for faster, more accurate proposals and seek practical, cost-effective AI solutions that ensure data privacy and security.
In conversations with construction companies, a common challenge emerged: making sense of their historical project data to create proposals that are both faster and more accurate. Many firms recognize the potential of AI to streamline this process and add strategic value but have concerns about the costs of implementing AI solutions and the implications for data privacy and security. As a result, they’re looking for practical, affordable ways to harness their existing data and explore AI without compromising confidentiality or exceeding budget constraints.
SOLUTION
We built a simple chat bot to analyze data and return it in an understandable way, while keeping company data safe with minimal cost.
We developed a lightweight chatbot prototype powered by OpenAI to demonstrate how quickly AI can add value in the construction industry. Using a mock dataset tailored to construction projects, the chatbot analyzes data and delivers insights in a simple, easy-to-understand format. To protect company data, we leveraged OpenAI’s updated privacy policies, which ensure that submitted data isn’t used to train their models. Additionally, we optimized our application code to filter and limit the data sent to OpenAI’s APIs—helping keep operational costs low while still providing meaningful results.
RESULTS
Earthling Interactive created a sample concept to show clients how AI can be implemented in their business.
Earthling has developed a practical proof of concept that demonstrates just one of the many ways AI can create real value for businesses. This example not only showcases AI’s potential but also directly addresses common concerns around cost, complexity, and data privacy—making it easier for potential clients to see how AI could work for them.


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