FileAI leads the race in GenAI document processing

FileAI is an AI-Native Unstructured Data Processing Platform specializing in automating document processing workflows with AI. Read how privatesynapse.ai helped FileAI with the adoption of Generative AI.

Case Study

FileAI processes almost half a billion documents per year, with their products spanning across various markets such as US, Asia, EU, and India. One of the their most important operations when automating document processing is data extraction and data entry. As documents present one of the most complex unstructured data types, FileAI is always looking for ways to improve performance of their solutions. As Generative AI has positioned itself as a leading technology for unstructured data processing, FileAI collaborated with privatesynapse.ai to further improve their AI document processing capabilities.

The project started with the goal of improving the two key data extraction and data entry operations - optical character recognition and form filling. Optical character recognition (OCR) is the process of converting documents into machine-readable text which is used for all downstream operations. One of those operations is form filling which referes to the process of locating and extracting specific data from the document into a structured form for the purpose of data entry.

For both tasks the proposed solution included a combination of traditional ML systems and Generative AI. Privatesynapse.ai developed and trained LLM and VLM models coupled with Text Embedding models that drastically increased the OCR and form filling accuracy on complex documents spanning foreign langauges and alphabets. The spotlight of the project was enabling FileAI to additionally obtain a semantical representation of the documents such as was needed when documents contained visual elements such as images or graphs.

For developing the supporting AWS infrastructure of the solution we utilized the following AWS services: EC2, ECS, S3, RDS, Codepipeline, Lambda, Bedrock and Sagemaker. Scalability was supported with the utilization of AWS autoscaling. Additionally a monitoring solution was developed which allowed FileAI to see all AI model calls live.

The solution now serves the production workload of FileAI and benefits its customers. privatesynapse.ai continues to collaborate with FileAI on new AI technologies.

Working with Brando and his team has been fantastic for fileAI. He possesses deep knowledge of the AWS cloud platform, and has a progressive stance on AI applications, specifically generative AI. We are continuing to engage his team for future projects to support fileAI’s mission.

Christian Schneider
CEO FileAI