K262515 · Kneu Health Digital , Ltd. · GYD · Aug 20, 2026 · Neurology
Device Facts
Record ID
K262515
Device Name
Kneu Platform (V2)
Applicant
Kneu Health Digital , Ltd.
Product Code
GYD · Neurology
Decision Date
Aug 20, 2026
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 882.1950
Device Class
Class 2
Attributes
Software as a Medical Device, 3rd-Party Reviewed
Indications for Use
The Kneu Platform is intended to quantify the kinematics of movement disorder symptoms, including tremor and dyskinesia, in adults (45 years and older) with mild to moderate Parkinson's disease.
Device Story
Kneu Platform V2 is a standalone software medical device for Parkinson's disease management. It captures active tremor assessments via smartphone accelerometer and passive tremor/dyskinesia data via Apple Watch (using Apple's Movement Disorder APIs/MM4PD). Data are transmitted to a cloud-hosted backend for aggregation and storage. A clinician web dashboard displays active and passive motor signal trends, monitoring wear time, and medication context. The device also includes patient-facing medication reminders and step counting. It is used in home and clinical settings by patients and healthcare professionals. The device does not provide diagnostic or treatment recommendations; outputs are supplementary to clinical judgment. The system facilitates longitudinal tracking of symptom kinematics to support clinical decision-making.
Clinical Evidence
No new clinical studies were conducted. Performance is supported by equivalence to the Parky App (K220820) using the same Apple MM4PD algorithm. Passive monitoring performance metrics: Rank Correlation Coefficient=0.80 for tremor severity; P<0.001 for dyskinesia presence; 94% match with clinician expectations (Powers et al). Active tremor performance is unchanged from K250153: correlations of 0.92 (p<0.01) and 0.85 (p=0.002) against clinical standards.
Technological Characteristics
Standalone software platform; utilizes off-the-shelf smartphones and Apple Watch. Data transmission via secure cloud backend. Cybersecurity includes TLS encryption in transit, AES-256 at rest, and OAuth 2.0/JWT authentication. Software developed per IEC 62304; risk management per ISO 14971. Passive monitoring uses Apple's Movement Disorder Management (MM4PD) API.
Indications for Use
Indicated for adults 45+ years with mild to moderate Parkinson's disease to quantify kinematics of tremor and dyskinesia symptoms.
Regulatory Classification
Identification
A tremor transducer is a device used to measure the degree of tremor caused by certain diseases.
{0}
**FDA U.S. FOOD & DRUG**
ADMINISTRATION
August 20, 2026
Kneu Health Digital, Ltd.
% Dave Yungvirt
CEO
Third Party Review Group, LLC
1887 Whitney Mesa Dr.
Suite 1960
Henderson, Nevada 89014
Re: K262515
Trade/Device Name: Kneu Platform (V2)
Regulation Number: 21 CFR 882.1950
Regulation Name: Tremor transducer
Regulatory Class: Class II
Product Code: GYD, NXQ, ISD
Dated: July 20, 2026
Received: July 21, 2026
Dear Dave Yungvirt:
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
{1}
K262515 - Dave Yungvirt
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 13485 clause 8.3 (Nonconforming product), ISO 13485 clause 8.5.2 (Corrective action), and ISO 13485 clause 8.5.3 (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 ISO 13485 clause 7.5) and document changes and approvals in the Medical Device File (ISO 13485 clause 4.2.3).
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 (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-
{2}
K262515 - Dave Yungvirt
Page 3
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,
# Patrick Antkowiak -S
Patrick Antkowiak
Assistant Director
DHT5A: Division of Neurosurgical,
Neurointerventional, and
Neurodiagnostic Devices
OHT5: Office of Neurological and
Physical Medicine Devices
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
{3}
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)
Device Name
Kneu Platform V2
Indications for Use (Describe)
The Kneu Platform is intended to quantify the kinematics of movement disorder symptoms, including tremor and dyskinesia, in adults (45 years and older) with mild to moderate Parkinson's disease.
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.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
# *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.*
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services
Food and Drug Administration
Office of Chief Information Officer
Paperwork Reduction Act (PRA) Staff
PRAStaff@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
FORM FDA 3881 (8/23)
Page of
PSC Publishing Services (301) 443-6740
EF
{4}
# Traditional 510(k) Summary
## Summary of Safety and Effectiveness
This summary of 510(k) safety and effectiveness information is submitted in accordance with 21 CFR 807.92. The summary retains the structure of the previous 510(k) Summary draft, but the content has been rebuilt from the current Kneu Platform Device Description and Substantial Equivalence rationale.
### Submitter Information
| Item | Information |
| --- | --- |
| Name | Kneu Health Digital Ltd. |
| Address | Blackwell House, Guildhall Yard, London, United Kingdom EC2V 5AE |
| Establishment Registration Number | 3032027298 |
| Owner/Operator Number | 10091292 |
| Phone | +44 0330 0430 939 |
| Contact | Alessia Nannetti, Quality and Regulatory Lead |
| E-mail | alessia.nannetti@kneu.com |
| Date of Summary | 20 July 2026 |
### Device Information
| Item | | Information | | |
| --- | --- | --- | --- | --- |
| Device Proprietary Name | | Kneu Platform V2 | | |
| Common Name | | Tremor Transducer | | |
| Trade Name | | Kneu Platform | | |
| Primary Product Code | | GYD | | |
| Additional product codes included for completeness | | NXQ medication reminder and ISD step count are supportive, informational functions. They are described for completeness and are not relied on to generate diagnostic or treatment recommendations. | | |
| Regulation Number (21 CFR) | Device | Product Class | Product Code | Classification Panel |
| 882.1950 | Tremor Transducer | Class II | GYD | Neurology |
### Substantial Equivalence
| Manufacturer | Trade Name | Regulation and Product Code | 510(k) Number | Use in this submission |
| --- | --- | --- | --- | --- |
| H2O Therapeutics | Parky App | 21 CFR 882.1950; GYD, NXQ, ISD | K220820 | Predicate for Apple Watch passive tremor and dyskinesia monitoring using Apple MM4PD / Movement Disorder APIs and for the supportive NXQ/ISD functions. |
| Neuhealth Digital Ltd. / Kneu Health Digital | Neu Platform / Kneu Platform | 21 CFR 882.1950; GYD | K250153 | Predicate for unchanged active smartphone-based tremor measurement, patient app, clinician |
Page 1
{5}
| | | | | dashboard, and cloud-hosted platform. |
| --- | --- | --- | --- | --- |
## Submission Description
This Traditional 510(k) describes a modification to the previously cleared Kneu / Neu Platform (K250153). The previously cleared active smartphone-based tremor assessment, patient smartphone application, clinician dashboard, and cloud infrastructure remain substantially unchanged. The modification adds passive tremor and dyskinesia monitoring for iOS users with a compatible paired Apple Watch. Passive outputs are generated by Apple's Movement Disorder APIs / MM4PD and transferred through the paired iPhone app to the Kneu backend and clinician dashboard. The submission also describes medication reminder (NXQ) and step count (ISD) functions as supportive, informational functions.
## Device Description
### General Description
The Kneu Platform V2 is a stand-alone software medical device platform intended for adults with mild to moderate Parkinson's disease and the healthcare professionals involved in their care. The platform captures active smartphone-based rest and postural tremor assessments, patient-reported information, medication information, and, for compatible iPhone/Apple Watch users, passive tremor and dyskinesia outputs generated by Apple's Movement Disorder APIs / MM4PD.
The platform comprises a patient smartphone app, a minimal bundled Apple Watch companion app used for passive-monitoring setup/status and local data transfer support, cloud-hosted backend services, and a clinician web dashboard. Kneu does not implement, train, or modify the Apple MM4PD algorithm. Passive monitoring is supplementary to active assessments and clinical judgement and does not generate diagnostic or treatment recommendations.
- Patient smartphone app: onboarding, active tremor assessments, patient-reported symptoms and questionnaires, medication diary/reminders, Apple Watch monitoring setup, and patient-facing insights.
- Apple Watch passive monitoring: background collection of tremor and dyskinesia outputs generated by Apple's Movement Disorder APIs / MM4PD, with local queueing and transfer to the paired iPhone app.
- Cloud-hosted backend: secure storage, aggregation, auditability, and retrieval of active and passive data for presentation.
- Clinician dashboard: presentation of active tremor information and a dedicated Passive Motor Signals / passive results area with tremor and dyskinesia trends, monitoring wear time, data availability, and medication-context indicators where applicable.
Page 2
{6}

Figure 1: High-level overview of the Kneu Platform from the Device Description.
### Intended / Indications for Use
The Kneu Platform is intended to quantify the kinematics of movement disorder symptoms, including tremor and dyskinesia, in adults (45 years and older) with mild to moderate Parkinson's disease.
### Comparison with the Predicate and Previously Cleared Device
The proposed device is substantially equivalent to the previously cleared Kneu / Neu Platform (K250153) for the unchanged active tremor functionality and substantially equivalent to Parky App (K220820) for Apple Watch passive tremor and dyskinesia monitoring. The comparison below summarizes the key characteristics.
| Characteristic | Subject Device - Kneu Platform V2 | Primary Predicate - Parky App (K220820) | Reference Predicate - Kneu / Neu Platform (K250153) | Equivalence |
| --- | --- | --- | --- | --- |
| Intended Use | To measure the degree of tremor and dyskinesia caused by certain diseases | To measure the degree of tremor and dyskinesia caused by certain diseases | To measure the degree of tremor caused by certain diseases | Equivalent to Primary Predicate |
| Indications for Use | The Kneu Platform V2 is intended to quantify the kinematics of movement disorder symptoms, | The Parky App is intended to quantify kinematics of movement disorder | The Kneu Platform is intended to quantify the kinematics of movement disorder | Substantially equivalent. The addition of dyskinesia measurement aligns the subject device |
Page 3
{7}
| | including tremor and dyskinesia, in adults (45 years and older) with mild to moderate Parkinson's disease. | symptoms including tremor and dyskinesia, in adults (45 years of age or older) with mild to moderate Parkinson's disease. | symptoms, including tremor in adults (45 years and older) with mild to moderate Parkinson's disease. | indications for use with Primary Predicate. Both Subject Device and Primary Predicate measure tremor and dyskinesia in the same patient population. |
| --- | --- | --- | --- | --- |
| Rx vs OTC | Rx | Rx | Rx | Equivalent |
| Use Environment | Home and clinic | Home and clinic | Home and clinic | Equivalent |
| Active Measurement Method | Accelerometer in commercial off-the-shelf smartphone | N/A (watch based only) | Accelerometer in commercial off the shelf digital device | Equivalent as Reference Predicate |
| Passive Measurement Method | Utilizes Apple's Movement Disorder Management (MM4PD) API and Apple Watch's accelerometer to measure and quantify dyskinesia and tremor | Utilizes Apple's Movement Disorder Management (MM4PD) API and Apple Watch's accelerometer to measure and quantify dyskinesia and tremor | N/A | Equivalent as Primary Predicate: same Apple Watch hardware class and Apple's Movement Disorder Management (MM4PD) API |
| Functionality | Active tremor assessment; passive tremor and dyskinesia monitoring; patient-reported information; medication reminders; step count. | Active tremor assessment and patient-reported information. | Passive tremor/dyskinesia monitoring; medication reminders; step count. | Combination of unchanged Reference Predicate functionality and Primary Predicate passive/supportive functionality. |
| Outputs and Features | Measure and quantify degree of tremor and dyskinesia; percentage of time tremor and dyskinesia were likely to occur | Measure and quantify degree of tremor and dyskinesia; percentage of time tremor and dyskinesia were likely to occur | Measure and quantify degree of tremor | Equivalent as Reference Predicate for active outputs; equivalent as Primary Predicate for passive outputs, medication reminders, and step count |
| Software | Software validation conducted as per FDA Guidance 'Content of Premarket Submissions for Device Software Functions', issued June 14, 2023 | Software validation conducted as per FDA Guidance 'Content of premarket submissions for Device Software Functions', issued May 11, 2005 | Software validation conducted as per FDA Guidance 'Content of premarket submissions for Device SoftwareFunctions', issued May 11, 2005 | Substantially equivalent |
| Cybersecurity | Cybersecurity threat analysis and mitigation conducted according to FDA cybersecurity guidance. Data encrypted in transit using TLS and at rest using AES-256. Patient and clinician access authenticated; APIs use OAuth 2.0/JWT authorization. Threat model updated for Apple Watch / Apple framework inputs, local queueing, and phone-to-cloud transfer pathway. | Cybersecurity threat analysis and mitigation has been conducted according to "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices". | Cybersecurity threat analysis and mitigation conducted according to "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices". Data encrypted TLS-1.2+ and AES-256. | Equivalent |
Page 4
{8}
| Performance data – Tremor and Dyskinesia | Device measurements highly correlated to clinical evaluations of tremor severity (Rank Correlation Coefficient=0.80) and mapped to expert ratings of dyskinesia presence (P<0.001). Symptom changes matched clinician expectations in 94% of evaluated subjects. (Powers et al Study) | Device measurements highly correlated to clinical evaluations of tremor severity (Rank Correlation Coefficient=0.80) and mapped to expert ratings of dyskinesia presence (P<0.001). Symptom changes matched clinician expectations in 94% of evaluated subjects. (Powers et al Study) | n/a | Equivalent – identical performance using Apple's Movement Disorder API |
| --- | --- | --- | --- | --- |
| Performance Data – Active Tremor | Device measurements highly correlated to clinical evaluations of tremor severity. Correlation of 0.92 (p<0.01) and 0.85 (p=0.002) between tremor measurement and clinical standard. | n/a | Device measurements highly correlated to clinical evaluations of tremor severity. Correlation of 0.92 (p<0.01) and 0.85 (p=0.002) between tremor measurement and clinical standard. | Equivalent – unchanged functionality |
| Patient Interface | Stand-alone software running on general purpose commercial off-the-shelf smartphones (iOS and Android), with iOS-only bundled Apple Watch companion app for passive monitoring setup/status and patient-facing Apple Watch results views. | Stand-alone software running on general purpose commercial off-the-shelf mobile smartphones. | Stand-alone software running on general purpose commercial off-the-shelf mobile smartphones. | Equivalent as Reference Predicate for existing smartphone app; equivalent as Primary Predicate for Apple Watch passive monitoring interface |
| Healthcare Professional Interface | Data stored in remote cloud databases. Information accessed by clinician via web portal, including active tremor outputs and passive tremor/dyskinesia dashboard module with time-based charts and data coverage context. | Data stored in remote central database (i.e., Cloud). Information accessed by clinician via web portal. | Data stored in remote central database (i.e., Cloud). Information accessed by clinician via web portal. | Equivalent; presentation is via web portal rather than email report and does not change the underlying measurement method |
Table 1: Comparison of characteristics between the Subject Device and predicate devices.
## Technological Characteristics
### Intended Use
The Subject Device and predicate devices quantify movement disorder symptoms in adults with mild to moderate Parkinson's disease. The existing active tremor assessment is unchanged from K250153. The
Page 5
{9}
passive tremor and dyskinesia monitoring uses the same Apple Watch hardware and Apple MM4PD / Movement Disorder API approach as K220820. Neither the Subject Device nor the predicate devices provide diagnosis or treatment recommendations.
## Principle of Operation and Technology Used
The Subject Device uses off-the-shelf smartphones for active assessments and, for compatible iOS users, an off-the-shelf Apple Watch for passive monitoring. Data are captured, transferred to the Kneu backend, securely stored and aggregated, and presented to patients and clinicians in human-readable visualizations. Passive tremor and dyskinesia data are supplementary to active assessments and clinical judgement.
## Software and Cybersecurity
The Subject Device uses software lifecycle, risk management, and cybersecurity controls described in the Device Description and Substantial Equivalence documents, including IEC 62304 software development, ISO 14971-aligned risk management, requirements traceability, verification and validation, cybersecurity threat assessment, encryption, access control, and labeling controls.
## Summary of Performance Data
Passive tremor and dyskinesia performance is supported by equivalence to Parky App (K220820), which uses the same Apple Watch hardware and Apple MM4PD / Movement Disorder API. Device measurements are highly correlated to clinical evaluations of tremor severity (Rank Correlation Coefficient = 0.80) and mapped to expert ratings of dyskinesia presence (P<0.001), with symptom changes matching clinician expectations in 94% of evaluated subjects (Powers et al). As the same Movement Disorder API is used, performance is identical to the predicate.
Active tremor performance remains based on the previously cleared Kneu / Neu Platform evidence and is unchanged. Device measurements are highly correlated to clinical evaluations of tremor severity, with correlations of 0.92 (p<0.01) and 0.85 (p=0.002) for rest and postural tremor measurements respectively against clinical standard assessments. This is equivalent to the predicate, with unchanged functionality.
Neither the Subject Device nor the predicate devices provide a diagnosis or treatment recommendation. Kneu presents passive outputs as supplementary trends and does not modify the MM4PD algorithm output into a diagnostic or treatment recommendation.
## Summary of Animal and Clinical Studies
Substantial equivalence is supported by comparison to the predicate devices and by non-clinical, software, and performance evidence. No new animal studies are included. No additional Kneu clinical study is required for the passive Apple Watch functionality because equivalence is based on the same Apple MM4PD algorithm and Apple Watch hardware used by Primary Predicate, together with Kneu software verification of integration, transfer, storage, aggregation, and display.
Page 6
{10}
# Conclusion
Based on the information presented in this Traditional 510(k) submission, the Kneu Platform V2 is substantially equivalent to the predicate devices, Kneu / Neu Platform (K250153) and Parky App (K220820), in intended use, technological characteristics, safety, performance, and risk profile. The Apple Watch passive monitoring functionality and supportive NXQ/ISD functions do not introduce new or different questions of safety or effectiveness.
Page 7
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
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.