How we supported an insurtech organization in training AI for accurate hazard detections
The story of an organization that is empowering insurance agencies and homeowners with AI
Our client is an insurance and construction expert passionate about using technology to keep homes healthy.
Based out of Florida, they aim to protect and improve home value with powerful AI technology that accurately detects potential hazards and helps homeowners with proactive home maintenance measures.
Services they outsourced to us: Data Annotation, quality checks, and customer support. Challenges faced by the client: Scaling AI development capabilities, managing and integrating data, IT support, customer service, and quality assurance. Why they chose us: Quality work, cost-effectiveness, market value, consistency, credibility, transparent reporting and analytics, data annotation skilled staff, and many more. |
When they chose to partner with us
1. Generated synthetic images to ensure data diversity
Our client initially contacted us regarding the requirement to annotate images depicting different aspects of home inspection.
We started by annotating home features like roof type, supply lines, switches, furnaces, valves, and more.
However, to train AI models accurately, we needed data diversity.
Although we had a large number of images depicting good home conditions, we lacked sufficient images representing wear and tear, maintenance issues, and functional deficiencies.
Hence, we preferred generating synthetic images to fill this data gap. But creating synthetic images that look realistic and match real-world conditions is a task on its own.
Thus, our team decided to leverage prompt engineering expertise and the latest image-generating tools to render 4,000 images that closely resembled real-life photographs.
2. Processed 6000 leads in 1 day
In the beginning, we were expected to annotate 2000 leads in 4 days. However, the continuous learning and training sessions, which start way before the client gets officially onboard, enabled us to process 6000 leads within just 24 hours, that is 1 day, exceeding expectations manifold.
Additionally, data classification played a crucial role, facilitating inspectors in generating detailed reports and recommendations. Historical data analysis further benefited inspection teams, enabling them to track changes over time, compare conditions across different inspections, and identify patterns in home conditions and maintenance needs.
3. Sustainable and eco-conscious efforts
“We are very pleased with how well you guys are processing the volume”
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