ROKAPAX vs. Fluency for Imaging

Our diverse selection of products includes VNA, PACS systems, Radiology Information Systems (RIS), Diagnostic Viewers, and AI-enhanced Medical Diagnostic Support Solutions (MDSS) specifically designed for modalities such as MMG, CT chest imaging, ECG, and X-ray endoprosthesis imaging. With a robust user base of over 300,000 active individuals each month and 20,000 diagnostic devices flawlessly integrated with our PACS|VNA, we take pride in offering state-of-the-art technological solutions that aim to improve patient care significantly. We are keen to impart our knowledge in the field of healthcare digitalization, which is focused on elevating patient experiences through optimized diagnostic workflows. Our dedication extends to promoting the seamless adoption of our solutions to enhance the efficiency of professionals such as radiologists, oncologists, and cardiologists in their daily tasks. Leveraging 14 years of collaboration with 5,000 clinics, we have honed our essential skills to create a comprehensive and flexible platform that addresses the entire imaging workflow, free from vendor limitations. Furthermore, our AI-powered medical decision support systems are crafted to effectively prioritize cases with identified pathologies on a single interface, employing a red-yellow-green alert system to bolster clinical decision-making. This groundbreaking method guarantees that healthcare practitioners can concentrate on what is most important: providing outstanding care to their patients, thereby fostering a healthcare environment that is more responsive and patient-centered. Ultimately, our innovations not only streamline processes but also facilitate better health outcomes for all involved.

Fluency for Imaging is an AI-powered radiology reporting platform developed by Jacobian to support faster, more accurate diagnostic reporting in medical imaging workflows. Radiology departments face increasing workloads and complex reporting requirements, which often lead to documentation inefficiencies and cognitive overload for clinicians. Fluency for Imaging addresses these challenges by combining advanced speech recognition technology, AI-driven automation, and structured reporting capabilities into a unified reporting environment. Radiologists can dictate reports using natural speech while the platform automatically organizes the narrative into structured clinical documentation. The system integrates directly with PACS platforms to transfer measurement data, imaging findings, and AI-generated insights directly into the report, eliminating manual transcription and reducing the potential for errors. Fluency for Imaging also incorporates large language model–based ambient reporting features that can listen to dictations, understand clinical context, and generate structured impressions automatically. Built-in guideline support and intelligent nudging help ensure reports follow established medical standards such as BI-RADS, PI-RADS, and TNM classifications. The platform also enables ontology-based coding using clinical standards including RadLex, SNOMED CT, and ICD-10, transforming unstructured text into structured, data-rich reports suitable for analytics, research, and clinical decision support. Multimedia reporting features allow radiologists to include annotated images, tables, and visual diagrams to improve report clarity for referring physicians. Additionally, Fluency for Imaging supports interoperability through standards such as HL7, FHIR, and FHIRcast, enabling seamless communication between imaging systems, hospital information systems, and analytics platforms.