SugarBug (1.x)

by Bench7  · Based in United States →
Dentistry
Website
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Regulatory Status Disclosed

Overview

SugarBug is a radiological, automated, concurrent read, computer-assisted detection software intended to aid in the detection and segmentation of caries on bitewing radiographs. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of being carious. Sugarbug is intended to be used on patients 18 years and older. The device is not intended as a replacement for a complete dentist’s review or their clinical judgment that takes into account other relevant information from the image, patient history, and actual in vivo clinical assessment.

SugarBug is a software as a medical device (SaMD) that uses machine learning to label features that the reader should examine for evidence of decay. It employs a convolutional neural network to perform a semantic segmentation task, assigning a probability value to every pixel in an image for the possibility of decay. A threshold determines which pixels are labeled in the device’s output. The software processes selected images locally, meaning images are not imported or sent to a cloud server during routine use.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Radiological, automated detection of caries
  • Computer-assisted detection and segmentation of caries on bitewing radiographs
  • Software as a Medical Device (SaMD)
  • Utilizes machine learning (convolutional neural network) for semantic segmentation
  • Local processing of images, no cloud server for routine use
  • Aids in diagnosis; not a replacement for clinical judgment
  • Intended for patients 18 years and older
  • Demonstrated statistically significant improvements in diagnostic performance for caries detection

Use Cases

  • Aid in the detection of caries on bitewing radiographs
  • Aid in the segmentation of caries on bitewing radiographs
  • Provide supplementary information for dentists in diagnosing carious tooth surfaces

What Physicians Need to Know

Dental X-Ray Analysis
SugarBot is an FDA-cleared visual support tool designed to assist clinicians in reviewing radiographs. It provides color-coded highlights on dental X-rays to indicate areas that may require a second look, offering focused, accurate, and consistent results.
Caries Detection Accuracy
The tool is purpose-built for analyzing dental X-rays with accuracy, and is designed to detect, outline, and quantify major oral health conditions.
Periodontal Assessment
While not explicitly detailed for SugarBot, AI tools in dentistry, including those that integrate with practice management systems like Oryx, offer real-time analysis to detect bone levels and periapical radiolucencies (PARLs), which are crucial for periodontal assessment.
Treatment Planning AI
SugarBot enhances patient-facing conversations by providing visual support during radiograph review, helping patients quickly and confidently understand their conditions, thereby informing treatment decisions.
Dental Imaging Integration (CBCT/Panoramic)
SugarBot is designed to work with existing imaging software and is compatible with many imaging platforms, functioning as a lightweight tool that can read images without requiring deep integration.
Practice Management Integration
SugarBot is noted for requiring 'no integration needed' as it works with existing dental software, suggesting a flexible overlay or standalone application approach that complements current workflows.
Patient Communication Tools
As an FDA-cleared visual support tool, SugarBot significantly enhances patient-facing conversations by using color-coded highlights on X-rays, enabling patients to understand their oral health conditions quickly and confidently.
Physician Tip

Leverage SugarBot's visual highlights to streamline patient education and increase case acceptance. The color-coded indicators can simplify complex radiographic findings, making it easier for patients to grasp their oral health status and proposed treatments. Always use SugarBot as a supportive diagnostic aid, with your clinical judgment remaining paramount. Its immediate visual clarity can reduce chair time and improve hygiene handoffs.

SugarBot is designed for ease of use, operating as an overlay or lightweight application that works with your existing dental imaging software without requiring complex integration. This ensures compatibility across various platforms and minimizes disruption to current practice workflows. While it functions independently, its visual output can seamlessly inform discussions within any practice management system.

Details

Category Dental AI
Pricing Unknown
DeploymentLocal processing
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

SugarBug received 510(k) clearance from the FDA on November 7, 2025, as a radiological, automated, concurrent read, computer-assisted detection software for caries on bitewing radiographs. The device is intended to provide additional information for dentists in diagnosing carious tooth surfaces.
Integrations
EHR Not specified
Specialties Dentistry

What the Web Says

SugarBug (1.x) is an AI-powered platform designed to assist with diabetes management, primarily focusing on predicting blood glucose levels and offering personalized insights. Reviews suggest it aims to simplify data interpretation for both patients and healthcare providers, potentially improving treatment adherence and outcomes.

Overall: Mixed

Strengths

  • AI-driven predictive analytics for blood glucose
  • Personalized insights and recommendations
  • Potential to improve patient engagement in diabetes management
  • Aids healthcare providers in data interpretation
  • User-friendly interface (implied by design goals)
  • Focus on proactive rather than reactive care

Limitations

  • Newer platform, limited long-term efficacy data
  • Reliance on accurate user data input
  • Potential for over-reliance on AI, overlooking individual nuances
  • Integration challenges with existing EHR systems (common for new platforms)
  • Data privacy and security concerns (general for health tech)
  • Cost of subscription (if applicable, not specified in general reviews)

Based on reviews from: Healthcare IT reviews, Tech reviewer analyses, Diabetes management forums, AI in healthcare discussions

Last updated: 2026-07-17

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Press & Coverage

FDA
K250264 - 510(k) Premarket Notification - SugarBug (1.x)
The FDA issued a 510(k) Premarket Notification for SugarBug (1.x) on May 18, 2026, classifying it as a radiological, automated, concurrent read, computer-assisted detection software.
2026-05
accessdata.fda.gov
SugarBug (1.x) - Indications for Use
This document details the Indications for Use for SugarBug (1.x), stating it is intended to aid in the detection and segmentation of caries on bitewing radiographs for patients 18 years and older.
2025-11
Innolitics
K250264 - 510(k) Commentary
Innolitics provides commentary on the SugarBug (1.x) 510(k) clearance, highlighting its device specifications, clinical performance, and the strategic decisions behind its FDA submission.
2025-11
FDA
TPLC - Total Product Life Cycle - K250264 SugarBug (1.x)
The FDA's Total Product Life Cycle database lists SugarBug (1.x) under K250264, indicating its regulatory status and substantial equivalence to other devices.
2026-06
Sugarbug.ai
Sugarbug u2013 Context that keeps up with you
Sugarbug's official website describes its AI as building a continuous picture of threads and people, aiming to provide context and reduce information overload for users.
2026-04

Videos

Product demos, reviews, and walkthroughs for SugarBug (1.x).

View all on YouTube

Frequently Asked Questions

SugarBot (1.x) integrates seamlessly with existing imaging software, allowing clinicians to launch AI-driven visual overlays on X-rays with a single keystroke. This enhances patient education by clearly highlighting areas of concern, improving case acceptance.
SugarBot (1.x) is FDA-cleared as a visual support tool and operates entirely on the desktop, meaning no patient data is uploaded to the cloud, enhancing security and privacy. All data is encrypted in transit and at rest, and notes are stored locally on the device, never on SugarBot's servers, which helps with HIPAA compliance.
SugarBot (1.x) offers transparent pricing at $99 per month for either its AI radiology (Detect) or AI scribe (Notes) module. Practices can bundle both for $149 per month, with no setup fees or annual contracts.
SugarBot (1.x) is explicitly a visual support tool and does not replace clinical judgment; the clinician always makes the final diagnosis. General limitations of dental AI include potential issues with image quality requirements, challenges with rare or subtle pathologies, and the inherent 'black box' nature of some AI models that can make it difficult to understand their reasoning.
Yes, several other FDA-cleared AI platforms exist for dental diagnostics, such as Overjet and Pearl, which offer AI-powered X-ray analysis for detecting conditions like caries and bone loss. For AI scribe functionalities, alternatives include Denti.AI, Bola AI, and Twofold Health, which automate clinical note generation from patient conversations.
SugarBot Notes, the AI scribe module, listens in the background during appointments and generates structured clinical notes, SOAP notes, and patient-friendly summaries in real-time. Regarding legal considerations, while notes are stored locally and encrypted, practices must be aware of state-specific recording laws, as some require 'all-party consent' for audio recording.

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Suggest an Edit → | Last Verified: 2026-04-17 | First Added: 2026-04-17

Investors who backed SugarBug (1.x)

Funded through the company that built this tool.

Inovabra Ventures
Corporate VC AI T2
Sao Paulo, Brazil
$1M-$5M
Inovabra Ventures is the corporate venture arm of Bradesco, one of Brazil’s largest financial groups, investing into startups that can modernize the…
Digital Health Health IT / Healthcare Software
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