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LANCERProject Description
A forward-looking real estate solutions provider, focused on improving property search and client engagement, approached Oodles to strengthen their AI-driven capabilities. The company sought to fine-tune large language models and computer vision systems for real estate data and imagery, enabling smarter insights and accurate outputs tailored to the industry.
Scope Of Work
The client sought Oodles for domain-specific AI models that combined text and image analysis, supported by Retrieval-Augmented Generation (RAG) for fact-based results. The scope covered fine-tuning LLMs, optimizing computer vision workflows, and building an evaluation pipeline to ensure accuracy and reliability.
Our Solution
Oodles implemented a tailored AI framework that unified advanced language understanding with image-driven property analysis. The approach involved fine-tuning large language models to grasp real estate-specific vocabulary and context while enhancing computer vision models to process images of listings, layouts, and property attributes.
Key Features Delivered:
- Domain-Focused LLM Fine-Tuning: Trained models to generate accurate property descriptions, handle client queries, and interpret contracts in real estate language.
- Enhanced Computer Vision Models: Enabled automated analysis of property images, layouts, and documents to extract valuable insights.
- Retrieval-Augmented Generation (RAG): Integrated retrieval mechanisms for fact-checked, context-rich responses.
- Evaluation Pipeline: Established metrics-based monitoring to measure accuracy, reliability, and ongoing improvements.