If you need a tool that lets you build your own models and transformations for processing and extracting data from documents with maximum precision and security, ABBYY is a top contender. This digital transformation platform uses AI, NLP and OCR to automate business processes. It can incorporate custom-built AI models and integrates with Robotic Automation (RAG), so it's well suited for automating document-handling tasks like accounts payable and customer onboarding. ABBYY has high capture accuracy and can handle complex fields, and it offers a low-code/no-code interface for citizen developers.
Another contender is Gilio, an information retrieval system that's designed to pull and transform structured information out of documents like financial statements and identity documents. Gilio uses methods like LLMs and visual analysis for high precision and offers API-first integration, customizable transformations and scalable security on AWS. It's geared for developers and businesses trying to automate document processing securely and efficiently.
Dataloop is another top contender, a full-featured AI development platform that includes data curation, model management and pipeline orchestration. It can handle many types of unstructured data and includes human feedback integration and strong security controls that meet GDPR, ISO 27001 and SOC 2 Type II standards. Dataloop can speed up development and improve collaboration across an organization.
If you prefer a more developer-focused approach, Sensible offers an API-first document processing service that makes it easier to extract data from many types of documents. It includes sophisticated parsing technology and a range of APIs for easy integration, along with elastic scalability and premium security. Sensible can extract data from many sources and includes more than 150 preconfigured parsers, making it a good choice for automating document processing needs.