Enterprise Data Is Trapped

75% of enterprise data is locked in unstructured formats — PDFs, spreadsheets, images, and scanned documents that are difficult for AI systems to process. As companies race to adopt large language models, the bottleneck isn't the models themselves but getting data into a format they can use. Existing tools like Amazon Textract and manual pipelines fail to deliver the accuracy and scale enterprises need.

What They're Building

Pulse transforms unstructured documents into structured, LLM-ready data. Born from the founders' experience building large-scale AI systems at Tesla and NVIDIA, Pulse offers production-grade document extraction that outperformed Amazon Textract and OpenAI o1 in a 12,000-document benchmark. The platform has processed over 600 million pages and serves as an AWS Bedrock integration partner.

Pulse raised a $3.9M seed round and was part of Y Combinator's Summer 2024 batch, validating its approach to solving one of enterprise AI's most persistent challenges.

Growth

Pulse is deployed at major enterprises including Samsung, Cloudera, and Howard Hughes. The company's AWS Bedrock integration gives it distribution across Amazon's cloud customer base, while its benchmark-beating accuracy drives adoption among teams that need reliable document extraction at scale.