The Fitbit ECG App is a software-only mobile medical application intended for use with Fitbit wrist wearable devices to create, record, store, transfer, and display a single channel electrocardiogram (ECG) qualitatively similar to a Lead I ECG. The Fitbit ECG App determines the presence of atrial fibrillation (AFib) or sinus rhythm on a classifiable waveform. The AFib detection feature is not recommended for users with other known arrhythmias. The Fitbit ECG App is intended for over-the-counter (OTC) use. The ECG data displayed by the Fitbit ECG App is intended for informational use only. The user is not interpret or take clinical action based on the device output without consultation of a qualified healthcare professional. The ECG waveform is meant to supplement rhythm classification for the purposes of discriminating AFib from normal sinus rhythm and not intended to replace traditional methods of diagnosis or treatment. The Fitbit ECG App is not intended for use by people under 22 years old.
Device Story
Software-only mobile medical application; operates on Fitbit wrist-worn devices and companion mobile app. Inputs: electrical potential differences from wrist-worn sensors. Processing: 30-second ECG recording analysis via algorithm to classify rhythm as AFib, sinus rhythm, or inconclusive. Outputs: ECG waveform (PDF) and rhythm classification displayed on mobile app. Used by patients (OTC) in home/non-clinical settings. Healthcare providers review output to supplement clinical diagnosis; not for independent clinical action. Benefits: enables patient-initiated rhythm monitoring to assist in AFib detection.
Clinical Evidence
Prospective clinical study (n=475) across 9 US sites. Subjects with/without AFib history underwent simultaneous 30-second 12-lead ECG and Fitbit ECG App recording. Primary endpoints: AFib detection sensitivity/specificity and morphological equivalence to Lead I. Results: 98.7% sensitivity, 100% specificity for AFib detection; 95.0% morphological equivalence to 12-lead Lead I tracings.
Technological Characteristics
Software-only application; utilizes electrical sensors on consumer wrist-worn hardware. Connectivity: local storage on wearable, transmission to mobile app/server. Standards: IEC 60601-2-47:2012, ANSI/AAMI EC57:2012. Output: single-channel Lead I ECG waveform. Classification: Class II, Product Code QDA.
Indications for Use
Indicated for individuals 22 years or older to record, store, and display a single-channel Lead I ECG and detect atrial fibrillation (AFib) or sinus rhythm. Not for users with other known arrhythmias. For OTC use; informational purposes only.
Regulatory Classification
Identification
An electrocardiograph software device for over-the-counter use creates, analyzes, and displays electrocardiograph data and can provide information for identifying cardiac arrhythmias. This device is not intended to provide a diagnosis.
Special Controls
In combination with the general controls of the FD&C Act, the electrocardiograph software for over-the-counter use is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) Clinical performance testing under anticipated conditions of use must demonstrate the following:
(i) The ability to obtain an electrocardiograph of sufficient quality for display and analysis; and
(ii) The performance characteristics of the detection algorithm as reported by sensitivity and either specificity or positive predictive value.
(2) Software verification, validation, and hazard analysis must be performed. Documentation must include a characterization of the technical specifications of the software, including the detection algorithm and its inputs and outputs.
(3) Non-clinical performance testing must validate detection algorithm performance using a previously adjudicated data set.
(4) Human factors and usability testing must demonstrate the following:
(i) The user can correctly use the device based solely on reading the device labeling; and
(ii) The user can correctly interpret the device output and understand when to seek medical care.
(5) Labeling must include:
(i) Hardware platform and operating system requirements;
(ii) Situations in which the device may not operate at an expected performance level;
(iii) A summary of the clinical performance testing conducted with the device;
(iv) A description of what the device measures and outputs to the user; and
(v) Guidance on interpretation of any results.
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA text logo on the right. The text logo has the FDA acronym in a blue square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue.
September 11, 2020
Fitbit, Inc. Shruti Rajagopalan Medical Regulatory Compliance Manager 199 Fremont Street San Francisco, California 94105
Re: K200948
Trade/Device Name: Fitbit ECG App Regulation Number: 21 CFR 870.2345 Regulation Name: Electrocardiograph software for over-the-counter use Regulatory Class: Class II Product Code: ODA Dated: August 10, 2020 Received: August 11, 2020
Dear Shruti Rajagopalan:
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 (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 located 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.
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
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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 of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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-device-safety/medical-device-reportingmdr-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/medicaldevices/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-device-advice-comprehensive-regulatoryassistance/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
Jennifer Shih Kozen Acting Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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## Indications for Use
510(k) Number (if known) K200948
Device Name Fitbit ECG App
#### Indications for Use (Describe)
The Fitbit ECG App is a software-only mobile medical application intended for use with Fitbit wrist wearable devices to create, record, store, transfer, and display a single channel electrocardiogram (ECG) qualitatively similar to a Lead I ECG. The Fitbit ECG App determines the presence of atrial fibrillation (AFib) or sinus rhythm on a classifiable waveform. The AFib detection feature is not recommended for users with other known arrhythmias.
The Fitbit ECG App is intended for over-the-counter (OTC) use. The ECG data displayed by the Fitbit ECG App is intended for informational use only. The user is not interpret or take clinical action based on the device output without consultation of a qualified healthcare professional. The ECG waveform is meant to supplement rhythm classification for the purposes of discriminating AFib from normal sinus rhythm and not intended to replace traditional methods of diagnosis or treatment. The Fitbit ECG App is not intended for use by people under 22 years old.
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------|
|-------------------------------------------------|
Prescription Use (Part 21 CFR 801 Subpart D)
X Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/3/Picture/0 description: The image shows the Fitbit logo. The logo consists of a stylized, geometric shape made up of small circles on the left side. To the right of the shape is the word "fitbit" in a sans-serif font. There is a registered trademark symbol to the right of the word.
# 510(k) SUMMARY
| Submitter | Fitbit, Inc<br>199 Fremont Ave, 14th Floor,<br>San Francisco, CA 94105 |
|-----------------------|------------------------------------------------------------------------|
| Contact Person: | Shruti Rajagopalan |
| Phone: | 408-242-2515 |
| Email: | shruti.rajagopalan@fitbit.com |
| Date Prepared: | 09 September 2020 |
| Name of Device: | Fitbit ECG App |
| Common or Usual Name: | Heart Rhythm Assessment, ECG |
| Regulation Number: | 21 CFR§870.2345 |
| Regulation Name: | Electrocardiograph software for over-the-counter use |
| Regulatory Class: | Class II |
| Product Code: | QDA |
| Submission Number | K200948 |
#### Predicate Device Information:
| Name of Device: | ECG App |
|-----------------|-------------|
| Manufacturer: | Apple, Inc. |
De Novo Petition Number: DEN180044
#### Indications for Use
The Fitbit ECG App is a software-only mobile medical application intended for use with Fitbit wrist-wearable devices to create, record, store, transfer, and display a single channel
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Image /page/4/Picture/0 description: The image shows the Fitbit logo. The logo consists of a stylized, geometric shape made up of small circles arranged in a pattern resembling a stylized "F". To the right of the geometric shape is the word "fitbit" in a sans-serif font. The logo is simple, modern, and easily recognizable.
electrocardiogram (ECG) qualitatively similar to a Lead I ECG. The Fitbit ECG App determines the presence of atrial fibrillation (AFib) or sinus rhythm on a classifiable waveform. The AF detection function is not recommended for users with other known arrhythmias.
The Fitbit ECG App is intended for over-the-counter (OTC) use. The ECG data displayed by the Fitbit ECG App is intended for informational use only. The user is not intended to interpret or take clinical action based on the device output without consultation of a qualified healthcare professional. The ECG waveform is meant to supplement rhythm classification for the purposes of discriminating AFib from normal sinus rhythm and not intended to replace traditional methods of diagnosis or treatment. The Fitbit ECG App is not intended for use by people under 22 years old.
### Device Description
The Fitbit ECG App is a software-only medical device used to create, record, display, store and analyze a single channel ECG. The Fitbit ECG App consists of a Device application ("Device app") on a consumer Fitbit wrist-worn product and a mobile application tile ("mobile app") on Fitbit's consumer mobile application. The Device app uses data from electrical sensors on a consumer Fitbit wrist-worn product to create and record an ECG. The algorithm on the Device app analyzes a 30 second recording of the ECG and provides results to the user. Users are able to view their past results as well as a pdf report of the waveform similar to a Lead I ECG on the mobile app.
#### Summary of Technological Characteristics
| | Subject Device<br>Fitbit ECG App | Predicate Device<br>Apple ECG app |
|---------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | K200948 | DEN180044 |
| Indications for<br>Use | The Fitbit ECG App is a<br>software-only mobile medical<br>application intended for use with<br>Fitbit wrist-wearable devices to<br>create, record, store, transfer, and<br>display a single channel<br>electrocardiogram (ECG)<br>qualitatively similar to a Lead I<br>ECG. The Fitbit ECG App<br>determines the presence of atrial | The ECG app is a software-only<br>mobile medical application<br>intended for use with the Apple<br>Watch to create, record, store,<br>transfer, and display a single<br>channel electrocardiogram (ECG)<br>similar to a Lead I ECG. The ECG<br>app determines the presence of<br>atrial fibrillation (AFib) or sinus<br>rhythm on a classifiable waveform. |
| | fibrillation (AFib) or sinus rhythm<br>on a classifiable waveform. The<br>AFib detection feature is not<br>recommended for users with other<br>known arrhythmias.<br>The Fitbit ECG App is intended for<br>over-the-counter (OTC) use. The<br>ECG data displayed by the Fitbit<br>ECG App is intended for<br>informational use only. The user is<br>not intended to interpret or take<br>clinical action based on the device<br>output without consultation of a<br>qualified healthcare professional.<br>The ECG waveform is meant to<br>supplement rhythm classification<br>for the purposes of discriminating<br>AFib from normal sinus rhythm<br>and not intended to replace<br>traditional methods of diagnosis or<br>treatment. The Fitbit ECG App is<br>not intended for use by people<br>under 22 years old. | The ECG app is not recommended<br>for users with other known<br>arrhythmias<br>The ECG app is intended for<br>over-the-counter (OTC) use. The<br>ECG data displayed by the ECG<br>app is intended for informational<br>use only. The user is not intended<br>to interpret or take clinical action<br>based on the device output without<br>consultation of a qualified<br>healthcare professional. The ECG<br>waveform is meant to supplement<br>rhythm classification for the<br>purposes of discriminating AFib<br>from normal sinus rhythm and not<br>intended to replace traditional<br>methods of diagnosis or treatment.<br>The ECG app is not intended for<br>use by people under 22 years old. |
| Mechanism of<br>Operation | Uses input from consumer<br>wrist-worn devices to detect the<br>electrical potential differences<br>between the electrical sensors and<br>generate an ECG waveform. | Uses input from consumer<br>wrist-worn devices to detect<br>electrical potential differences<br>between the electrodes and the<br>crown and generate an ECG<br>waveform. |
| Device<br>Classification | Class II | Class II |
| FDA Product<br>Code and<br>Regulatory<br>Classification | QDA<br>21 CFR 870.2345 | QDA<br>21 CFR 870.2345 |
| Anatomical sites | Left hand fingers to right wrist or<br>vice versa on a consumer grade<br>electronic. | Left hand fingers to right wrist or<br>vice versa on a consumer grade<br>electronic. |
| Patient<br>population | Individuals (22 years or older) | Individuals (22 years or older) |
| Data storage | ECG data stored locally on<br>wrist-worn device until<br>transmission to a server. | ECG data stored locally on<br>wrist-worn device until<br>transmission to a server. |
| Prescription/OTC | OTC | OTC |
| ECG Channels | Single Channel, Lead I | Single Channel, Lead I |
| User Interface | Device app and Mobile app | Device app and Mobile app |
| Use Method | Record a 30 second ECG on the<br>wrist-worn device and receive<br>results determining the presence of<br>Atrial Fibrillation or Normal Sinus<br>Rhythm. | Record a 30 second ECG on the<br>wrist-worn device and receive<br>results determining the presence of<br>Atrial Fibrillation or Normal Sinus<br>Rhythm. |
| Results of the<br>algorithm | Atrial Fibrillation<br>Normal Sinus Rhythm<br>Inconclusive | Atrial Fibrillation<br>Normal Sinus Rhythm<br>Inconclusive |
| ECG Waveform<br>Display | Qualitatively similar to a Lead I<br>ECG waveform displayed as a pdf<br>on the Mobile app | Similar to a Lead I ECG displayed<br>as a pdf on the Mobile app |
### Table 1. Subject and Predicate Device Comparison
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## Non-clinical Testing
All necessary performance testing was conducted on the Fitbit ECG App to support a determination of substantial equivalence to the predicate device. This testing included testing of input signal quality as per IEC 60601-2-47:2012 Medical Electrical Equipment -Ambulatory Electrocardiographic Systems. Testing was conducted using appropriate databases from ANSI/AAMI EC57:2012.
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Image /page/7/Picture/0 description: The image shows the Fitbit logo. The logo consists of a stylized, geometric shape made up of small circles arranged in a pattern resembling a stylized letter 'F' or a diamond shape. To the right of the geometric shape is the word "fitbit" in a sans-serif font. A small circle with an 'R' inside is located to the right of the word.
## Human Factors Testing
Human Factors testing was performed to demonstrate that the user can correctly use the device by solely reading the device labeling and also correctly interpret the device output and understand when to seek medical care. This testing satisfies the special control requirements of the predicate device and provides evidence of substantial equivalence.
## Clinical Testing
Clinical testing was performed similar to the predicate device. 475 subjects, with and without a known diagnosis of AFib, were recruited to participate across 9 US sites. Eligible subjects underwent a 10-second screening using a 12-lead ECG. Subjects with a known history of AFib were screened for AFib by a single qualified physician and assigned to the AFib cohort. Subjects without a known history of AFib were screened for NSR and assigned to the NSR cohort. Subsequently, subjects underwent a simultaneous 30-second 12-lead ECG and Fitbit ECG App test. The Fitbit ECG App software algorithm was able to detect AF with the sensitivity and specificity of 98.7% and 100%, respectively. The Fitbit ECG App's single lead waveform was deemed morphologically equivalent to the Lead I of a 12-Lead ECG waveform overall for 95.0% of AF and SR tracings reviewed qualitatively. The qualitative and quantitative results of the clinical study demonstrated substantial equivalence.
### Conclusions
The Fitbit ECG App is similar in technological characteristics and has the same intended use as the Apple ECG app. Differences in technological characteristics have been evaluated through performance testing including the special controls requirements of the predicate which has shown that the minor technological differences between the Fitbit ECG App and the predicate device raise no new issues of safety or effectiveness. Bench and clinical data demonstrate that the Fitbit ECG App is substantially equivalent to the Apple ECG App.
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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.
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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
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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.
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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.
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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.
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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.