fileAI: turning data bottlenecks into business advantage

fileAI is collaborating with AWS to transform manual data cleanup into automated, reliable workflows that can scale across enterprises.

Enterprise data is often unstructured. It may not fit into standard formats or live in neat tables, and for multinational companies, may be in multiple languages and reside in systems in numerous geographies. As such, it’s difficult to manage, impacting workflows, compliance efforts and the ability to extract valuable insights.

fileAI makes this data manageable, enabling organizations to prepare, validate, and assess unstructured data quickly and reliably for use in AI workflows. Built on AWS, its platform features proprietary AI components which automate critical data management tasks, reducing manual work and accelerating and automating operations. Critically, fileAI operates at scale, processing hundreds of millions of files annually to support global enterprises.

This global reach demands not only the capacity to handle vast data volumes but also an architecture that can scale efficiently as workloads grow.  “The choice for us to work with AWS is based around the focus on the startup segment and the emphasis on scalability across microservices,” says Claire Leighton, co-founder and chief operating officer, fileAI.

Reducing time and resources

The startup is leveraging a number of AWS services and solutions to power its platform, support its customers, and “scale to hundreds of millions of files annually,” says Leighton. These include  Anthropic’s AI model, Claude, via Amazon Bedrock; serverless compute service, AWS Lambda; managed database service, Amazon Aurora; security and DDoS protection service, AWS Shield; content delivery network service, Amazon CloudFront; and Amazon SageMaker for data, analytics, and AI.

With Amazon Bedrock, fileAI is leveraging a range of tools and “state-of-the-art” AI and ML models for building generative AI application and agents, accelerating data processing times for its customers. fileAI’s platform replaces manual processes with automation, resulting in “an 80% reduction in time spent processing insurance claims and a 10% reallocation of workforce to more high impact tasks,” says Leighton.

Maximizing efficiency and security

fileAI is also delivering robust security for enterprises, many of which may be managing sensitive data or operating in regulated industries. Amazon Bedrock encrypts data in transit and at rest, offers comprehensive monitoring and logging capabilities to support data governance requirements, and enables full control over data. “By bringing privacy-focused AI to fileAI through Claude in Amazon Bedrock, we are achieving accuracy and performance of our models that exceeds anything else in the market,” says Leighton.

Finally, the scalable microservices architecture from AWS has enabled fileAI to achieve 28x more accurate data processing than legacy optical character recognition tools. The AWS architecture is scalable to demand, meaning fileAI only invests in the resources it needs. As such, says Leighton, “the relationship with AWS allows us a cost-effective way to scale.”

Preparing for an AI future

fileAI is enabling customers to transform data preparation from a bottleneck into a competitive advantage. By utilizing well-architected cloud infrastructure from AWS, fileAI has achieved scalable, efficient workflows that not only accelerate customer success but also fuel the company’s growth. As the demand for AI-driven data solutions continues to rise, fileAI’s collaboration with AWS will enable it to meet the evolving needs of enterprises. As such, says Leighton, “We look forward to a continued partnership”—one that will drive further innovation as it scales for the future.

To learn more about cutting-edge developments in AI and data processing, join fileAI and other industry leaders at AWS re:Invent. Register now for the Las Vegas event and discover how cloud technologies and community can help your startup scale.