Onymos, developer of solutions transforming Software-as-a-Service (SaaS) for software and application development, has announced the release of an enhanced version of its intelligent document processing component, DocKnow.

The latest version offers a new ability to integrate customer-specific large language models (LLMs), enabling enterprises to extract, process, and validate data from documents with precision and speed.

Onymos DocKnow eliminates the need for time-intensive and error-prone manual data processing by using enhanced optical character recognition (OCR) to extract information from both structured and unstructured data.

This includes printed and handwritten text, numbers, dates, checkboxes, barcodes, QR codes, and more from any document, including personal identification, intake forms, and health and immunization records. DocKnow can also be easily integrated with any third-party back-end information management system – such as Salesforce, AWS, Azure, and Google – or health record system.

In this latest version, DocKnow is strengthened by:

• A new customer-specific LLM API: This new API enables enterprises to train their own LLMs using their specific data, resulting in more accurate and domain-specific document processing. For instance, DocKnow reliably and instantly identifies inconsistent data across hundreds of pages.
• A new, helpful AI assistant: "Doc," the Onymos AI agent, enables document processing teams – which could include healthcare professionals, legal teams, university registrars, and more – to search through specific documents and hundreds of pages for immediate access to particular information and records.
• An upgraded, customizable user interface (UI): The new, simple UI includes bounding boxes, automatic zoom-in/zoom-out, image enhancement, and skew correction, which dramatically improves readability for human reviewers. It allows full customization to match an enterprise's brand, required functionality, and back-end systems. This gives enterprise software engineering and IT teams the ability to modify the component to meet their specific needs as if they had built it from the ground up themselves.

"We understand that many enterprises struggle with time-consuming and error-prone processes like document entry, validation, and retrieval, whether it's for patient care, student registration, or case file review. While these enterprises have started integrating AI tools powered by LLMs like ChatGPT to help with these activities, they often encounter hallucinations and outdated training data issues," said Shiva Nathan, Founder and CEO of Onymos.

"Our enhanced DocKnow addresses these challenges by streamlining document processing and empowering enterprises to train their own LLM models tailored to their specific needs, all while ensuring privacy and security."

As with all Onymos software components, DocKnow is designed with a no-data architecture. This means that all data passing through the solution and used to train the LLM remains securely with the enterprise using the API – no bit or byte of data flows through any Onymos systems or clouds.

You can also learn more about Onymos' no-data architecture by downloading the white paper here.

https://onymos.com/