Enlitic

What is Enlitic?

Enlitic is a medical technology company founded in 2014, pioneer in applying deep learning to medical imaging and clinical data analysis. The company focuses on solving one of healthcare's biggest problems: the lack of standardization and consistency in clinical data generated by imaging machines (such as X-rays, CT scans, and MRIs) from different manufacturers.

How it works

Enlitic acts as an intelligent layer between imaging scanners and PACS (Picture Archiving and Communication System) databases. By reading DICOM image metadata, Enlitic's AI automatically identifies, corrects, and standardizes descriptions and tags. Additionally, it analyzes the pixel content of images to automatically prioritize exams with critical findings and pre-format reports.

Key features

• ENDEX: Module that reads, translates, and standardizes DICOM data headers to create consistent nomenclatures across equipment brands and hospitals.
• ENLISE: Clinical intelligence tool that extracts relevant clinical data from textual reports and imaging reports, structuring them for predictive analysis.
• Triage and Prioritization: Automated classification that places urgent cases (such as hemorrhages or severe fractures) at the top of radiologists' workflows.
• PACS/RIS Integration: Native and transparent integration into doctors' existing clinical workflows without requiring complex new screens.

Available integrations

Enlitic integrates directly with major global PACS, RIS, and Electronic Health Record (EHR) providers through health interoperability standards such as HL7 and DICOM, ensuring that hospitals can use the AI within their internal networks without changing their core software infrastructure.

Who it is for

• Hospitals and imaging clinics that process large volumes of exams and want to reduce cataloging and billing errors.
• Radiologists who need auxiliary tools for fast detection and triage of pathologies in clinical images.
• Healthcare IT managers focused on standardizing corporate clinical medical data.

Real use cases

1. Clinical Dictionary Standardization: Hospital networks use Enlitic to convert millions of old exams with inconsistent names into a clean, standardized database for clinical research.
2. Reduction in Triage Time: Hospitals use automatic exam triage to accelerate response times in emergency medical care.

Pricing

Pros and cons

Pros:

• High precision in standardizing complex DICOM protocol metadata.
• Helps unify clinical data from multiple healthcare units.
• Reduces the administrative workload of radiologists.

Cons:

• Complex initial implementation requiring strict compliance with local healthcare security regulations (such as LGPD/HIPAA).
• Exclusively targeted at the large-scale hospital market (B2B).

Alternatives to Enlitic

Key alternatives in the AI medical imaging and radiology segment include:

• Aidoc: Widely used real-time clinical triage AI platform in radiology.
• Arterys: Cloud-based solution for exam viewing and image analysis with AI.
• Lunit: Artificial intelligence focused on oncology and early detection of cancer through imaging.