Behold.ai

Chest X-ray and CT triage AI

SF7.3
Coordinate care for time sensitive casesRadiology departments and health systems
Coordinate care for time sensitive casesRadiology departments and health systems

Best for

Radiology departments and health systems

Pricing

Custom

SoftFinders Score

7.3 / 10

Overview

What is Behold.ai?

Behold.ai develops AI medical imaging software centred around red dot®, a clinical decision-support platform that analyzes medical images to help radiology teams prioritize urgent findings and identify examinations that are highly likely to be normal. The technology is primarily designed to support chest X-ray and CT head workflows by helping clinicians manage reporting demand and focus attention on cases requiring review.


  1. Clinical imaging support: red dot® analyzes chest X-rays for potential abnormalities and supports CT head pathways by helping identify urgent findings and high-confidence normal examinations. It is designed as a decision-support tool that assists radiologists rather than replacing clinical interpretation.
  2. Workflow integration: the platform is designed to operate within existing radiology environments by connecting with systems such as PACS and RIS, allowing imaging analysis results to be delivered within established reporting workflows rather than requiring clinicians to use a separate application.
  3. AI deployment model: Behold.ai uses deep-learning-based medical imaging algorithms trained for specific clinical pathways, with solutions focused on targeted use cases rather than general-purpose image interpretation across all modalities.
  4. Implementation considerations: healthcare organizations should evaluate regulatory status in their region, local clinical validation requirements, imaging infrastructure compatibility, governance processes, and how AI-supported prioritization fits into existing radiology operations.


Behold.ai is most suitable for healthcare providers looking to introduce AI-assisted image triage into radiology workflows where reducing reporting delays and prioritizing clinically important cases are key operational goals.

KEY FEATURES

What you get out of the box

Worklist Integration

Integrates flagged studies into radiologist worklist

Multi Modality

Supports CT, MRI, X-ray, and related modalities

Care Coordination

Routes alerts to relevant care team members

Reporting Support

Drafts or supports impressions and report language

Imaging Workflow

Connects across PACS and reading environments

Outcome Tracking

Tracks downstream care actions from flagged studies

USE CASES

Where teams put it to work

Coordinate care for time-sensitive cases
Support reporting language consistency
Triage screening exams at scale
Reduce missed findings on busy lists
Bridge imaging and downstream pathways
Track outcomes from flagged studies

Editorial Take

What we like, and what to verify

What we like
  • Rapid normal versus abnormal chest triage
  • Stays focused on real radiology buyer problems
  • Scales to organization-wide healthcare rollouts
What to verify
  • Clearance scope varies by region
  • Radiologist confirmation required on every study
  • Pricing is sales-led and needs scoping upfront

FAQ

Quick answers

DECISION TIME

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