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Title
First American Data & Analytics fine-tunes open-source LLMs on Databricks, cutting extraction costs 70%
…mmercial models. It was also more affordable than running on those big models.” In fact, the team was able to achieve a cost savings of 70% compared with a previous implementation using a different model. Additionally, Databricks’ serverless compute and Model Serving eliminated previ…
Description
First American Data & Analytics (DNA), a property-centric information provider to the real estate and title insurance industries, used the Databricks Data + AI Platform to fine-tune open-source LLMs (Mistral, Llama 3, Llama 3.1) for page-level classification and extraction of 100+ data fields from roughly 4 million historical title policy images dating to the 1930s. Using Delta Lake, Databricks Model Training, Managed MLflow, and serverless Model Serving on about 50 GPUs, the team fine-tuned models in two weeks versus the two-plus months it previously took on other platforms. The project cut extraction costs by 70%, reduced project completion time by 75% (months to weeks), and increased the number of data elements extracted tenfold.
…and cost savings while increasing the number of data elements extracted by 10x. With Databricks, DNA reduced the time needed to complete data extraction projects by 75%, going from several months to just weeks. By moving to Databricks serverless compute for their model serving, DNA elimina…
…d with GPU usage but also provided scalability to handle large volumes of data. The fine-tuning of models — which previously took over two months on other platforms — was achieved in just two weeks with Databricks. This acceleration in project timelines allowed First American DNA to handle dat…
Company
First American Data & Analytics
…t 75% Less time to complete the project 10x Increase in data elements extracted First American Data & Analytics (DNA), a leading property-centric information provider to the real estate and title insurance industries, was challenged to convert a vast amount of unstructured data into digital cont…
Industry
Real Estate
…10x Increase in data elements extracted First American Data & Analytics (DNA), a leading property-centric information provider to the real estate and title insurance industries, was challenged to convert a vast amount of unstructured data into digital cont…
Problem
First American Data & Analytics maintains the industry's largest data repository of publicly recorded document images, over 8 billion unstructured documents, most stored with very limited metadata. The team received a set of roughly 4 million historical title policy images dating to the 1930s that needed page-level classification and extraction of more than 100 data elements per page, and earlier LLM approaches required huge training datasets and long fine-tuning times for these complex use cases.
…tral to their parent company’s broader title and transaction closing processes. This division maintains the industry’s largest data repository of publicly recorded document images, with over 8 billion unstructured documents. Most of these historical documents are stored with very limited (if any) metada…
…d, “Even though we already use many language models in our production pipeline, earlier models required huge training datasets and time for fine-tuning for our complex use cases. We were looking for a process that required less training data, reduced the ti…
Solution
Working with Databricks, First American DNA fine-tuned several open-source LLMs, including Mistral, Llama 3 and Llama 3.1, using Databricks Model Training on Delta Lake for data storage, Managed MLflow to streamline the LLM lifecycle, and roughly 50 GPUs for training; fine-tuned models were registered in Unity Catalog, and serverless Model Serving eliminated GPU-availability bottlenecks for deployment.
…with our DevOps processes.” Building on the foundation provided by Delta Lake, the DNA team utilized Databricks Model Training to fine-tune several open source models, including Mistral, Llama 3 and Llama 3.1, and is now testing Llama 3.2 with their enterprise data. This fine-tuning appr…
…he LLM lifecycle, improving the efficiency of the handling of potential errors, while running training workloads on approximately 50 GPUs. Prabhu elaborated, “First American Data & Analytics is continually seeking out…
Business value
The fine-tuning approach cut extraction costs by 70% compared with a previous implementation, reduced data-extraction project time by 75% (from several months to weeks), and increased the number of data elements extracted tenfold; the fine-tuning step itself, which previously took over two months, was completed in two weeks.
…mmercial models. It was also more affordable than running on those big models.” In fact, the team was able to achieve a cost savings of 70% compared with a previous implementation using a different model. Additionally, Databricks’ serverless compute and Model Serving eliminated previ…
…and cost savings while increasing the number of data elements extracted by 10x. With Databricks, DNA reduced the time needed to complete data extraction projects by 75%, going from several months to just weeks. By moving to Databricks serverless compute for their model serving, DNA elimina…
Implementation approach
The Databricks team gave First American DNA early access to Databricks Model Training and met almost daily to co-write and debug code, completing fine-tuning of the open-source models in about two weeks.
…s continually seeking out new technologies for the betterment of our customers; the Databricks team helped us get early access to Databricks Model Training for fine-tuning and literally had meetings almost every day with us, writing and debugging the code together. We were able to do this in a couple of weeks, testing out a couple of open source models and fine-tuning them, so they were…
AI capabilities
Document Intelligence
…d data into digital content and match the data to related properties. To do so, they sought to implement page-level classification and strategic extraction across 100+ data fields. An early adopter of NLP and vision models, the First American Data & Analytics…
Technology
Delta Lake, Unity Catalog, Mistral, Llama 3
…s post Details Industry : Financial Services Use Case : Artificial Intelligence Product : Agent Bricks , Delta Lake , Unity Catalog Ready to get started? Try Databricks for free Learn more about our product Talk…
Deployment model
cloud
…compared with a previous implementation using a different model. Additionally, Databricks’ serverless compute and Model Serving eliminated previous bottlenecks associated with GPU availability and scalability. This serverless approach enabled the DNA team to deploy LLMs at scale without t…
Deployment options
cloud
…compared with a previous implementation using a different model. Additionally, Databricks’ serverless compute and Model Serving eliminated previous bottlenecks associated with GPU availability and scalability. This serverless approach enabled the DNA team to deploy LLMs at scale without t…
Headline outcome
…mmercial models. It was also more affordable than running on those big models.” In fact, the team was able to achieve a cost savings of 70% compared with a previous implementation using a different model. Additionally, Databricks’ serverless compute and Model Serving eliminated previ…
Use case type
Document processing
…l improvement, the DNA team sought to deploy new and additional technologies to extract information from images of documents like deeds, mortgages, assignments and foreclosures that vary widely in quality. The title insurance process requires extensive res…
