CoLumbo C-Spine is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM cervical spine Magnetic Resonance (MR) images for users' review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements: - Segmentation of the vertebrae (C3-C7) and disks (C2C3-C7T1); - Measurements based on the segmentation; - Threshold-based labeling of out-of-range measurement; and - Export of measurement results. CoLumbo C-Spine does not produce or recommend any type of medical diagnosis or treatment. The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. Instead, CoLumbo C-Spine simply helps users to more easily identify and classify features in cervical MR images and potentially compile a report. The user is responsible for confirming/modifying settings, reviewing the software-generated measurements, utilizing CoLumbo C-Spine's output using their medical judgment and discretion. The device is intended to be used only by hospitals and other medical institutions. Only DICOM MR images of the spine of patients aged 22 and above with adequate visualization of C2–C7 are considered to be valid input. Performance has not been established in the presence of vertebral enumeration variants that may interfere with reliable vertebral counting, including true cervical ribs, hemivertebrae, congenital or acquired vertebral fusion, for images acquired with contrast media, for cases involving tumors, infections, post-operative changes, or vertebral fusion, or for examinations in which the C2 vertebra is not adequately visualized.
Device Story
CoLumbo C-Spine is an image post-processing software tool for cervical spine MRI. It takes previously acquired DICOM MR images as input; performs automated segmentation of vertebrae (C3-C7) and disks (C2C3-C7T1) using rule-based algorithms; calculates quantitative measurements; and applies user-defined thresholds to label out-of-range findings. Used in hospitals/medical institutions by radiologists, neurosurgeons, and spine surgeons. The software output serves as a starting point for clinical workflow, assisting in visualization and report compilation. It does not provide diagnosis or treatment recommendations. Clinicians review, confirm, or modify software-generated measurements and settings using their professional judgment. The device benefits patients by streamlining the measurement process and identifying potential abnormalities for clinical review.
Clinical Evidence
Bench testing and software performance assessment study conducted in the U.S. using 95 MRI cervical spine studies. Performance compared against ground truth defined by 4 radiologists. Results: Vertebral body height MAE 0.72 mm (95% CI 0.56-0.88); Disk height MAE 0.90 mm (95% CI 0.76-1.05); Tissue segmentation Dice Similarity Coefficient (MDC) for vertebral body 0.90 (95% CI 0.86-0.93) and disk 0.84 (95% CI 0.81-0.87). Cybersecurity validated via vulnerability assessment and penetration testing.
Technological Characteristics
Software-only medical image management and processing system. Operates on DICOM MR images. Employs rule-based algorithms for segmentation and measurement. Features include threshold-based labeling of out-of-range measurements and export functionality. No hardware components. Cybersecurity controls implemented to prevent unauthorized access/modification.
Indications for Use
Indicated for skeletally mature patients aged 22+ requiring quantitative cervical spine MR image analysis. Contraindicated for patients with vertebral enumeration variants (e.g., cervical ribs, hemivertebrae, fusions), tumors, infections, post-operative changes, or cases where C2 is not adequately visualized. Not for use with contrast-enhanced images.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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FDA U.S. FOOD & DRUG ADMINISTRATION
April 1, 2026
Smart Soft Healthcare AD
Yoana Ivanova
Regulatory Affairs Director
113 General Kolev St., Primorski District., Office 7.2
Varna, 9002
Bulgaria
Re: K254015
Trade/Device Name: CoLumbo C-Spine
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QIH
Dated: March 4, 2026
Received: March 4, 2026
Dear Yoana Ivanova:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K254015 - Yoana Ivanova
Page 2
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13484 clause 8.3 (Nonconforming product), and ISO 13485 clause 8.5 (Corrective and preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the Quality Management System Regulation (QMSR) (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn
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K254015 - Yoana Ivanova
Page 3
(https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,

For:
Jessica Lamb, Ph.D.
Assistant Director
Imaging Software Team
DHT8B: Division of Radiological Imaging Devices and Electronic Products
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below.
510(k) Number (if known)
K254015
Device Name
CoLumbo C-Spine
Indications for Use (Describe)
CoLumbo C-Spine is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM cervical spine Magnetic Resonance (MR) images for users' review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements:
- Segmentation of the vertebrae (C3-C7) and disks (C2C3-C7T1);
- Measurements based on the segmentation;
- Threshold-based labeling of out-of-range measurement; and
- Export of measurement results.
CoLumbo C-Spine does not produce or recommend any type of medical diagnosis or treatment. The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. Instead, CoLumbo C-Spine simply helps users to more easily identify and classify features in cervical MR images and potentially compile a report. The user is responsible for confirming/modifying settings, reviewing the software-generated measurements, utilizing CoLumbo C-Spine's output using their medical judgment and discretion.
The device is intended to be used only by hospitals and other medical institutions.
Only DICOM MR images of the spine of patients aged 22 and above with adequate visualization of C2–C7 are considered to be valid input. Performance has not been established in the presence of vertebral enumeration variants that may interfere with reliable vertebral counting, including true cervical ribs, hemivertebrae, congenital or acquired vertebral fusion, for images acquired with contrast media, for cases involving tumors, infections, post-operative changes, or vertebral fusion, or for examinations in which the C2 vertebra is not adequately visualized.
Type of Use (Select one or both, as applicable)
☑ Prescription Use (Part 21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
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"DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW."
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PISC Publishing Services (301) 443-6740
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CoLumbo C-Spine
510(k) Premarket Notification
Smart Soft Healthcare
K254015
# 510(k) Summary
## 1. Submitter
Smart Soft Healthcare AD
Address: 113 General Kolev Str., Primorski District., Office 7.2 Varna 9002, Bulgaria
Phone: +359 52 919 513
Fax: None
Contact Person: Yoana Ivanova
Date Prepared: April 1, 2026
## 2. Subject Device
Name of Device: CoLumbo C-Spine
Common or Usual Name: Automated Radiological Image Processing Software
Classification Name: Medical image management and processing system (21 CFR 892.2050)
Product Code: QIH
Regulatory Class: II
## 3. Predicate Device
Device Name: CoLumbo
Manufacturer: Smart Soft Healthcare AD
Classification Name: Medical image management and processing system (21 CFR 892.2050)
Classification Product Code: QIH
Classification Panel: Radiology
Device Class: Class II
510(k) Number: K241211 cleared August 15, 2024
## 4. Device Description
CoLumbo C-Spine is a medical device (software) for assisting in the viewing and interpretation of magnetic resonance imaging (MRI) of the cervical spine. The software is an assistive tool that helps users to identify and measure c-spine features in medical images. The segmentation and measurements provided by the software are classified based on rule-based algorithms, and thresholds set by each software user and stored in the user's individualized software settings.
The purpose of CoLumbo C-Spine is to provide information regarding different c-spine measurements. The software automatically initiates measurements resulting from segmentation of the vertebrae (C3-C7) and disks (C2C3-C7T1). Segmentations serve the purpose of calculating measurements. User-defined/confirmed settings control the software per individual user's preference for annotating features in an image that may have out-of-range measurements.
The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. The output is an aid to the clinical workflow of measuring
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CoLumbo C-Spine
510(k) Premarket Notification
Smart Soft Healthcare
patient anatomy and should not be misused as a diagnosis tool. CoLumbo C-Spine does not produce or recommend any type of medical diagnosis or treatment. Instead, it simply helps users to more easily identify and classify features in c-spine MR images and potentially compile a report. The user is responsible for confirming/modifying settings, reviewing the software-generated measurements, and utilizing CoLumbo C-Spine output using their medical judgment and discretion.
# 5. Indications for Use
CoLumbo C-Spine is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM cervical spine Magnetic Resonance (MR) images for users' review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements:
- Segmentation of the vertebrae (C3-C7) and disks (C2C3-C7T1);
- Measurements based on the segmentation;
- Threshold-based labeling of out-of-range measurement; and
- Export of measurement results.
CoLumbo C-Spine does not produce or recommend any type of medical diagnosis or treatment. The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. Instead, CoLumbo C-Spine simply helps users to more easily identify and classify features in cervical MR images and potentially compile a report. The user is responsible for confirming/modifying settings, reviewing the software-generated measurements, utilizing CoLumbo C-Spine's output using their medical judgment and discretion.
The device is intended to be used only by hospitals and other medical institutions.
Only DICOM MR images of the spine of patients aged 22 and above with adequate visualization of C2-C7 are considered to be valid input. Performance has not been established in the presence of vertebral enumeration variants that may interfere with reliable vertebral counting, including true cervical ribs, hemivertebrae, congenital or acquired vertebral fusion, for images acquired with contrast media, for cases involving tumors, infections, post-operative changes, or vertebral fusion, or for examinations in which the C2 vertebra is not adequately visualized.
# 6. Comparison of the Technological Characteristics with the Predicate Device
In comparison to the Predicate Device, the Subject Device provides comparable outputs in terms of segmentation, measurement and labeling. A tabular high-level comparison of the Subject Device and the Predicate Device is provided as Table 1 below.
Table 1 – Comparison of Technological Characteristics with Predicate Device
| | Predicate Device (K241211) | Subject Device | Remark/Discussion |
| --- | --- | --- | --- |
| Device Name | CoLumbo | CoLumbo C-Spine | n/a |
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CoLumbo C-Spine
510(k) Premarket Notification
Smart Soft Healthcare
| Manufacturer | Smart Soft Healthcare | Smart Soft Healthcare | n/a |
| --- | --- | --- | --- |
| Classification Panel | Radiology | Radiology | Same |
| CFR Section | 21 CFR 892.2050
(Medical image management and processing system)
QIH | 21 CFR 892.2050
(Medical image management and processing system)
QIH | Same |
| Device Class | Class II | Class II | Same |
| Intended Use | Intended to assist the radiologist, spine- and neuro-surgeon in performing routine evaluations of lumbar spine MRI exams and producing a report of findings summarizing the results of the evaluation. | Intended to assist the radiologist, spine- and neuro-surgeon in performing routine evaluations of cervical spine MR images. | Similar |
| Indications for Use | CoLumbo is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM lumbar spine Magnetic Resonance (MR) images for users’ review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements:
• Feature segmentation;
• Feature measurement;
• Threshold-based labeling of out-of-range measurement; and
• Export of measurement results to a written report for user’s review, revise and approval.
CoLumbo does not produce or recommend any type of medical diagnosis or treatment. Instead, it simply helps users to more easily identify and classify features in lumbar MR images and compile a report. The user is responsible for confirming/modifying settings, reviewing and verifying the software-generated measurements, inspecting out-of-range measurements, and approving draft report content using their medical judgment and discretion.
The device is intended to be used only by hospitals and other medical institutions. Only DICOM images of MRI acquired from lumbar spine exams of patients aged 18 and above are considered to be valid input.
CoLumbo does not support DICOM | CoLumbo C-Spine is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM cervical spine Magnetic Resonance (MR) images for users’ review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements:
• Segmentation of the vertebrae (C3-C7) and disks (C2C3-C7T1);
• Measurements based on the segmentation;
• Threshold-based labeling of out-of-range measurement; and
• Export of measurement results.
CoLumbo C-Spine does not produce or recommend any type of medical diagnosis or treatment. The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. Instead, CoLumbo C-Spine simply helps users to more easily identify and classify features in cervical MR images and potentially compile a report. The user is responsible for confirming/modifying settings, reviewing the software-generated measurements, utilizing CoLumbo C-Spine's output using their medical judgment and discretion.
The device is intended to be used only by hospitals and other medical institutions. | Similar |
Page 3 of 5
{7}
CoLumbo C-Spine
510(k) Premarket Notification
Smart Soft Healthcare
| | images of patients that are pregnant, undergo MRI scan with contrast media, or have post-operative complications, tumors, infections. | Only DICOM MR images of the spine of patients aged 22 and above with adequate visualization of C2–C7 are considered to be valid input. Performance has not been established in the presence of vertebral enumeration variants that may interfere with reliable vertebral counting, including true cervical ribs, hemivertebrae, congenital or acquired vertebral fusion, for images acquired with contrast media, for cases involving tumors, infections, post-operative changes, or vertebral fusion, or for examinations in which the C2 vertebra is not adequately visualized. | |
| --- | --- | --- | --- |
| Intended User | Radiologist & neuro- and spine-surgeons | Radiologist & neuro- and spine-surgeons | Same |
| Intended Patient Population | The intended patient population is not subject to any restrictions. Automation support requires images of patients of 18 years and older, not pregnant, without post-operative complications, tumors, infections. | Skeletally mature patients of age 22 and older that are not pregnant and do not have fusions, post-operative complications, tumors, infections. | Highly Similar |
| Supported Body Part | Lumbar spine | Cervical spine | Similar – different parts of the spine |
| Threshold-Based Out-of-Range Measurements | Yes | Yes | Same |
| Supported Modality | MR | MR | Same |
The Subject Device is substantially equivalent in comparison to the Predicate Device. The information regarding the Subject Device does not raise new questions about safety and effectiveness, and demonstrates that CoLumbo C-Spine is at least as safe and effective as its predicate device CoLumbo.
## 7. Performance Data
Smart Soft Healthcare has performed software design verification testing and has sponsored external software performance assessment study. The performance data demonstrates continued conformance for medical devices containing software.
Smart Soft Healthcare conforms to the cybersecurity requirements by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed or transferred from a medical device to an external recipient. The vulnerability assessment and penetration testing demonstrate satisfactory security performance with no critical and high-risk vulnerabilities.
## Software Performance Validation
To validate the CoLumbo C-Spine software from a clinical perspective, a software performance
Page 4 of 5
{8}
CoLumbo C-Spine
510(k) Premarket Notification
Smart Soft Healthcare
assessment study was conducted in the U.S. The software performance assessment study included 95 MRI c-spine studies for 95 patients of different gender, ages and racial groups. The performance assessment study compared the CoLumbo C-Spine software outputs to the ground truth defined by 4 radiologists on segmentations and measurements.
| Measurement | MAE | 95% CI |
| --- | --- | --- |
| Vertebral body height | 0.72 mm | (0.56, 0.88 mm) |
| Disk height | 0.90 mm | (0.76, 1.05 mm) |
| Disk material outside of the intervertebral space AP size | 0.72 mm | (0.52, 0.92 mm) |
| Focal disk material outside of the intervertebral space AP-size | 1.29 mm | (0.94, 1.63 mm) |
| Tissue Segmentation | MDC | 95% CI |
| --- | --- | --- |
| Vertebral body (sagittal) | 0.90 | (0.86, 0.93) |
| Disk (sagittal) | 0.84 | (0.81, 0.87) |
| Disk material outside of the intervertebral space (sagittal) | 0.70 | (0.68, 0.73) |
| Focal disk material outside of the intervertebral space (axial) | 0.68 | (0.64, 0.72) |
# 8. Conclusions
The CoLumbo C-Spine software is as safe and effective as its predicate device. The subject device has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences between subject and predicate device do not alter the intended use of the device and do not raise new or different questions regarding its safety and effectiveness when used as labeled.
The software verification and validation testing data, including the standalone software performance assessment study data, supports the safety of the devices and demonstrates that the CoLumbo C-Spine software performs as intended in the specified use conditions.
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.