The Replit Team
Problem Statement
Christo Hefer is Founder and COO at Symplete, a real estate technology platform for agents to handle marketing and sales and help agents select the best purchase agreements for their listings. He wanted to create a prototype where a residential purchase agreement could be uploaded in PDF format and analyzed using OpenAI’s GPT-3 API. Based on 15-20 different fields as inputs, the best purchase agreement should be recommended to the agent.
Building the Prototype
To do this, the Bounty Hunter Syed (Repit username: cudanexus) used a Python Library to read the residential agreement PDF before sending it to GPT-3 to analyze. After that, he used the GPT-3 API to analyze the document and present the real estate agent with the optimal agreement for their listing. The parameters used included the address, price and offer expiry dates amongst others.
Benefits
Bounties gave Christo a quick way to validate his idea. He was able to develop a prototype to collect usage data which was then used to inform the roadmap for the product his company is building. This product will assist real estate agents in reviewing and organizing incoming purchase agreements, thus cutting down on their time drastically.
In Christo’s words, “After Syed delivered the prototype we knew what we wanted to achieve was possible and started building the full product immediately. It’s coming along great. For the full product, we again turned to Replit Bounties.”
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