Guardoc uses Amazon Nova to transform medical documents into actionable data

Startup Guardoc has developed a solution that combines Amazon Nova language models with Amazon Bedrock platform to automate the processing of medical documents. Instead of relying on manual review of medical records and reports, the technology extracts structured information reliably, reducing errors and accelerating clinical flows.

How does processing medical documents with Amazon Nova work?

The Guardoc system uses the Amazon Nova models – a family of LLMs optimized for natural language tasks – to interpret unstructured documents such as recipes, examinations and historical. Integration with Amazon Bedrock allows the solution to perform inferences without the need to manage its own infrastructure. The process includes steps of entity recognition, data classification and validation based on configurable confidence limits. AWS published a detailed article on implementation on the official blog.

Why is precision crucial in the processing of medical documents?

Medical documents contain critical information: diagnoses, allergies, dosages. An extraction error could compromise treatments. Guardoc has established a benchmarking process that compares the results of the models with human annotations, defining trust thrills for each type of data. According to AWS, the approach significantly reduces false positives in fields such as drug names and ICD codes. The trend of health automation is also reflected in other areas – as seen in AI adoption by major brands to manage global operations.

What practical guidelines does AWS recommend for benchmarking in medical document processing?

In the post, AWS suggests three steps: 1) create a validation dataset with actual annotated documents, 2) run Amazon Nova models with different temperature and top-p parameters, and 3) measure accuracy, recall and F1-score for each information category. The definition of confidence limits should be calibrated according to the criticality of the field – for example, a higher limit for medical records than for clinical observations.

How to configure confidence limits in the processing of medical documents?

The Guardian has implemented a panel that allows dynamically adjusting the threshold. If the trust of an extraction is below the limit, the document goes for human review. This hybrid logic maintains efficiency without sacrificing security. The company also recommends the use of Amazon Bedrock for logging and continuous monitoring of results.

Frequently Asked Questions about Medical Document Processing

Do Amazon Nova models require custom training?

Yes, Guardoc recommends fine-tuning with medical domain-specific documents to get the best accuracy, but Amazon Bedrock already offers pre-trained models that can be used without immediate customization.

Can I use the solution without deep knowledge in AI?

The Guardoc platform abstracts the complexity of the models, allowing clinical teams to define validation rules and trust limits through a visual interface, without programming.

What is the estimated cost per processed document?

The cost depends on the volume and model chosen – smaller models such as Amazon Nova Lite are cheaper for simple tasks, while Nova Pro provides greater accuracy for complex documents. AWS suggests calculating the cost per thousand requests on the Amazon Bedrock portal.