Rad AI Unveils Next-Generation Speech Recognition That Redefines Radiology Reporting

Breakthrough technology delivers faster, more accurate reports through proprietary multi-model AI and advanced language understanding

Builds on Rad AI's broader reporting innovations, including its RSNA Ventures collaboration, to advance the next generation of radiology efficiency

CHICAGO, Dec. 1, 2025 /PRNewswire/ -- Rad AI, the leader in AI-powered radiology workflow solutions, today announced the launch of next-generation speech recognition technology (patent pending) that dramatically improves the speed and accuracy of diagnostic reporting. Integrated into Rad AI Reporting, the new capabilities deliver unprecedented speed and accuracy, setting a new standard for dictation in radiology.

This innovation reflects Rad AI's continued commitment to solving radiology's biggest bottlenecks – time, accuracy and documentation quality – by embedding intelligence directly into the workflow. The new system doesn't just transcribe words; it understands clinical context, recognizes uniqueness and adapts to how each radiologist works.

"The foundation of great radiology care is a fast, accurate report," said Doktor Gurson, CEO of Rad AI. "Today, radiologists are limited by reporting tools that simply transcribe words but don't understand the user behind them – still missing subtleties, struggling with clinical terminology, and forcing radiologists to spend valuable time correcting basic errors. We built this technology to understand context so that radiologists can return focus to diagnosis, not documentation."

Purpose-Built for Radiologists

Traditional speech recognition systems rely on a single application that often struggles with diverse accents, overlapping speech and the complexity of medical terminology. Rad AI's new multi-model architecture overcomes those limitations by combining multiple speech engines powered by Rad AI's proprietary modeling and unique "voting" algorithm that determines the most accurate understanding in real time.

This approach ensures consistent, high-fidelity results across all reading environments, from quiet reading rooms to challenging acoustic conditions, such as emergency department workstations. Fine-tuned language models handle radiology-specific terminology, measurements, modifiers and even context-based interpretation cues such as laterality and sequence timing.

In early evaluations of Rad AI's speech model, radiologists reported markedly fewer dictation errors, more natural transcription flow and a smoother experience overall.

"Every innovation we build starts from the same question: what slows radiologists down?" added Gurson. "From AI-driven impression generation to now speech intelligence, we're removing friction from the reporting process so radiologists can spend more time on what matters most – their patients."

Raising the Bar for Accuracy and Efficiency

By integrating workflow analytics, Rad AI's reporting engine goes beyond speech recognition,  where radiologists spend unnecessary time dictating redundant information, such as "pertinent negatives" or repeated phrases already captured in templates.

This intelligent feedback loop supports Rad AI's broader philosophy of "speak less, say more" – helping radiologists optimize both the quality and efficiency of their reports. Key advancements include:

• Multi-model precision: Proprietary algorithm dynamically compares multiple transcriptions simultaneously to select the most accurate output.
• Adaptive accuracy: Custom language models fine-tuned for radiology vocabulary and syntax.
• Workflow intelligence: Real-time analytics, highlighting opportunities to shorten dictation and streamline templates.
• Seamless integration: Sub-second, latency-free transcription within the existing Rad AI Reporting interface.

Advancing the Future of Reporting

This milestone builds on Rad AI's expanding ecosystem of workflow innovations, including its collaboration with RSNA Ventures to bring 100 years of peer-reviewed clinical guidance directly into the radiologist workflow. Together, these advancements underscore Rad AI's vision for the next chapter of radiology – one where reporting is faster, smarter, powered by AI and informed by real-world evidence.

By combining speech recognition, workday analytics and contextual insights, Rad AI is redefining what's possible in radiology reporting: fewer clicks, fewer words and more clarity in every report.

ARA Health Specialists went live with Rad AI Reporting and its AI-powered features in February 2025. In a recent analysis, 79% of ARA radiologists improved on efficiency as measured by median time spent on the report.

"Moving to Rad AI was 100% the right move for ARA Health, and it's advancing the way that our physicians practice medicine," said Joe Guiffrida, chief operations officer at ARA. "A transition like this requires a team that listens and responds with urgency. Rad AI has shown that level of partnership from day one. We are already seeing a meaningful impact that will shape how our physicians practice for years to come."

See it Live at RSNA 2025

Rad AI will showcase its enhanced speech recognition and reporting innovations at the 2025 Radiological Society of North America (RSNA) Annual Meeting, Booth #4753, with live demonstrations and interactive sessions throughout the event.

Rad AI will also be showcasing its products at "Radiology Reimagined: AI, innovation and interoperability in practice," an interactive exhibit that will demonstrate how radiology systems can be integrated to efficiently include and scale AI-based applications at key points in the workflow.

About Rad AI

Rad AI is the leader in generative AI solutions for radiology, transforming the way radiologists work and improving patient care. The company's flagship product, Rad AI Reporting, streamlines radiology reporting with AI-driven technology and empowers radiologists to achieve greater efficiency, accuracy and satisfaction. Rad AI Impressions, the company's pioneering product, established Rad AI as an innovator in generative AI for radiology; as the first generative AI application to achieve widespread adoption in radiology, it is now trusted by thousands of US radiologists. Rad AI Continuity, the most comprehensive solution of its kind, uses AI to help ensure patient follow-up for potential new cancers.

The company has been recognized as one of the most promising healthcare AI companies by CB Insights (Digital Health 50, AI 100) and AuntMinnie (Best New Radiology Software 2023, Best New Radiology Vendor 2021). In 2025, the company was selected as one of CNBC's Disruptor 50, which highlighted the most innovative companies in generative AI and ranked No. 107 on the annual Inc. 5000 list, the most prestigious ranking of the fastest-growing private companies in America.

Learn more about Rad AI at www.radai.com

SOURCE Rad AI