Pivotal study: 335 evaluable patients from six sites in the United States
>1 (expert clinicians)
Indications for Use
The EarliPoint System is intended for use by healthcare providers to objectively diagnose and assess children for ASD using software algorithm to analyze a child's response to an external stimulus in the form of videos.
Device Story
EarliPoint System uses eye-tracking hardware to capture visual response data from children viewing age-appropriate social videos; operator monitors session via remote module. Data is transmitted to a secure WebPortal where AI software analyzes looking behavior. System outputs ASD diagnosis and three developmental delay indices (Social Disability Index, Verbal Ability Index, Non-verbal Ability Index) that proxy ADOS-2 and Mullen scales. Used in clinical settings by healthcare providers; output assists clinicians in diagnostic decision-making; benefits include objective, standardized assessment for early ASD identification.
Eye-tracking module with remote operator module; WebPortal for data storage and analysis. Complies with IEC 60601-1 (electrical safety) and IEC 60601-1-2 (EMC). Software designed per IEC 62304. Non-invasive, continuous operation, Class I protection against electric shock, Type B applied part.
Indications for Use
Indicated for children ages 16 months through 30 months who are at risk for Autism Spectrum Disorder (ASD) based on concerns identified by a parent, caregiver, or healthcare provider, to aid qualified clinicians in diagnosis and assessment.
Regulatory Classification
Identification
A pediatric Autism Spectrum Disorder diagnosis aid is a prescription device that is intended for use as an aid in the diagnosis of Autism Spectrum Disorder in pediatric patients.
Special Controls
In combination with the general controls of the FD&C Act, the pediatric Autism Spectrum Disorder diagnosis aid is subject to the following special controls:
- (1) Clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use, including an evaluation of sensitivity, specificity, positive predictive value, and negative predictive value using a reference method of diagnosis and assessment of patient behavioral symptomology.
- (2) Software verification, validation, and hazard analysis must be provided. Software documentation must include a detailed, technical description of the algorithm(s) used to generate device output(s), and a cybersecurity assessment of the impact of threats and vulnerabilities on device functionality and user(s).
- (3) Usability assessment must demonstrate that the intended user(s) can safely and correctly use the device.
- (4) Labeling must include:
- (i) Instructions for use, including a detailed description of the device, compatibility information, and information to facilitate clinical interpretation of all device outputs:
- (ii) A summary of any clinical testing conducted to demonstrate how the device functions as an interpretation of patient behavioral symptomology associated with Autism Spectrum Disorder. The summary must include the following:
- (A) A description of each device output and clinical interpretation;
- (B) Any performance measures, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV);
- (C) A description of how the cut-off values used for categorical classification of diagnoses were determined; and
- (D) Any expected or observed adverse events and complications.
(iii)A statement that the device is not intended for use as a stand-alone diagnostic.
*Classification.* Class II (special controls). The special controls for this device are:(1) Clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use, including an evaluation of sensitivity, specificity, positive predictive value, and negative predictive value using a reference method of diagnosis and assessment of patient behavioral symptomology.
(2) Software verification, validation, and hazard analysis must be provided. Software documentation must include a detailed, technical description of the algorithm(s) used to generate device output(s), and a cybersecurity assessment of the impact of threats and vulnerabilities on device functionality and user(s).
(3) Usability assessment must demonstrate that the intended user(s) can safely and correctly use the device.
(4) Labeling must include:
(i) Instructions for use, including a detailed description of the device, compatibility information, and information to facilitate clinical interpretation of all device outputs; and
(ii) A summary of any clinical testing conducted to demonstrate how the device functions as an interpretation of patient behavioral symptomology associated with Autism Spectrum Disorder. The summary must include the following:
(A) A description of each device output and clinical interpretation;
(B) Any performance measures, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV);
(C) A description of how the cutoff values used for categorical classification of diagnoses were determined; and
(D) Any expected or observed adverse events and complications.
(iii) A statement that the device is not intended for use as a stand-alone diagnostic.
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March 26, 2025
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: on the left, there is an emblem of the Department of Health & Human Services, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The emblem features a stylized depiction of an eagle or other bird-like figure. The text is arranged in three lines, with "FDA" in a larger font size and a blue square behind it.
EarliTec Diagnostics, Inc. % Amy Wolbeck Regulatory Consultant ROM+ 2790 Mosside Blvd. Monroeville, Pennsylvania 15146
Re: K243891
Trade/Device Name: EarliPoint System Regulation Number: 21 CFR 882.1491 Regulation Name: Pediatric Autism Spectrum Disorder Diagnosis Aid Regulatory Class: Class II Product Code: OPF Dated: February 21, 2025 Received: February 24, 2025
Dear Amy Wolbeck:
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.
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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 System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 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 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-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 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-device-advicecomprehensive-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-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-regulatory
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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,
Jay R. Gupta -S
Jay Gupta 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
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## Indications for Use
| Submission Number (if known) | |
|------------------------------|--|
|------------------------------|--|
K243891
Device Name
EarliPoint
Indications for Use (Describe)
The EarliPoint System device is indicated as a tool to aid qualified clinicians in the diagnosis and assessment of Autism Spectrum Disorder (ASD) in children ages 16 months through 30 months, who are at risk based on concerns identified by a parent, caregiver, or healthcare provider.
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)
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# 510(K) SUMMARY
| 510(k) Information | |
|-----------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 510(k) Number | |
| 510(k) Type | Special 510(k) |
| Date Prepared | 18 December 2024 |
| Submitter Information | |
| 510(k) Submitter: | Ryan Bormann, Director of Quality and Operations<br>EarliTec Diagnostics, Inc.<br>13895 Industrial Park Blvd, Suite 140<br>Tel:+1-833-504-9937<br>Email: rbormann@earlitecdx.com |
| Primary Correspondent: | Amy Wolbeck<br>Regulatory Consultant<br>RQM+<br>2790 Mosside Blvd.<br>Monroeville, PA 15146<br>Tel:+1-707-291-3457<br>Email: awolbeck@rqmplus.com |
| EarliPoint System Device Information | |
| Trader Name (Common Name): | EarliPoint System Device |
| Device Classification Name | Pediatric Autism Spectrum Disorder Diagnostic Aid |
| Classification Regulation: | 21 CFR 882.1491 |
| Class: | II |
| Panel: | Neurology Devices Panel |
| Product Code: | QPF |
| Predicate Device | EarliPoint System K230337 |
| Device Description | The EarliPoint system uses an eye tracker to capture the patient's<br>looking behavior while viewing a series of videos. The system then<br>remotely analyzes the looking behavior data using software and<br>outputs a diagnosis of the patient's ASD status and associated<br>developmental delay indicies.<br>The EarliPoint System device consists of the following:<br>• Eye-tracking module and a separate Operator Module that can<br>control the Eye-tracking module remotely. The patient sits on a<br>chair and the Eye-tracking module is adjusted by the operator<br>such that the patient's eyes are within the specification of the<br>eye tracking window.<br>• Eye-tracking module captures the patient visual response to<br>social information provided in the form of a series of age-<br>appropriate videos.<br>• Operator's module is used to initiate and monitors the session<br>remotely<br>• WebPortal securely stores all patient information, analyzes the<br>eye tracking data, and outputs the results. Users can retrieve<br>the results directly from the web-portal.<br>• Artificial intelligence software analyzes the eye-tracking data and provides a diagnosis for ASD. In addition, it also outputs 3 |
| | developmental delay indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments Social Disability Index correlates and proxies ADOS-2 Verbal Ability Index correlates and proxies the age equivalent Mullen Verbal Ability score Non-verbal Ability Index correlates and proxies the age equivalent non-verbal Mullen Ability score |
| Intended Use | The EarliPoint System is intended for use by healthcare providers to objectively diagnose and assess children for ASD using software algorithm to analyze a child's response to an external stimulus in the form of videos. |
| Indications for Use | The EarliPoint System device is indicated as a tool to aid qualified clinicians in the diagnosis and assessment of Autism Spectrum Disorder (ASD) in children ages 16 months through 30 months, who are at risk based on concerns identified by a parent, caregiver, or healthcare provider. |
| EarliPoint System Nonclinical and Clinical Data (unchanged from predicate device) | |
| Performance Testing | EarliPoint was verified to meet the electrical safety standards and the software were designed and tested per IEC 62304. |
| Mechanical/Electrical Safety and<br>Electromagnetic Compatibility<br>(EMC) | Mechanical/electrical safety and EMC testing were conducted on the EarliPoint device. The EarliPoint device is classified as Class I for protection against electric shock with Type B applied part and is intended for continuous mode of operation. Compliance testing shows that the EarliPoint device complies with all the applicable tests of IEC 60601-1 standard for mechanical/electrical safety and the IEC 60601-1-2 standard for EMC. |
| Software Verification and<br>Validation | Software verification and validation testing were successfully completed. |
| Clinical Studies | The safety and effectiveness of the EarliPoint System in collecting eye tracking data and analyzing the data for the diagnosing the presence of ASD was evaluated in a pivotal study where patients were diagnosed by the device as well and expert clinicians (reference standard).<br><br>The pivotal study was a prospective, double-blind, multi-center, within-subject comparison where 500 patients from six sites in the United States were enrolled, of which 475 were evaluable for primary and secondary endpoint analysis and 25 patients had missing data of the device or the control diagnosis (standard of care).<br><br>All patients were evaluated for ASD by both the EarliPoint system and by expert clinician diagnosis (current best practice for diagnosis of ASD) to evaluate the sensitivity and specificity of the EarliPoint System diagnosis relative to the expert clinical diagnosis. The study also correlated the three EarliPoint Severity |
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| Population | Sensitivity<br>Mean (n/N)<br>95% CI | Specificity<br>Mean (n/N)<br>95% CI |
|-----------------------------------------------------------------------------------|-------------------------------------|-------------------------------------|
| EarliPoint (mITD)<br>N=475 | 71% (157/221)<br>64.6% - 76.9% | 80.7% (205/254)<br>75.3% - 85.4% |
| EarliPoint CertainDx<br>(Clinicians are<br>Certain of Diagnosis<br>only)<br>N=335 | 78.0% (117/150)<br>70.5%, 84.3% | 85.4% (158/185)<br>79.5% - 90.2% |
# SUBSTANTIAL EQUIVALENT COMPARISON
| Device<br>Characteristic | Predicate Device K230337<br>EarliPoint System | Subject Device<br>EarliPoint System |
|--------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use | The EarliPoint System is intended for use<br>by healthcare providers to objectively<br>diagnose and assess children for ASD<br>using software algorithm to analyze a<br>child's response to an external stimulus in<br>the form of videos. | Same as predicate |
| Indications for<br>Use | The EarliPoint System is indicated for<br>use in specialized developmental<br>disabilities centers as a tool to aid<br>clinicians in the diagnosis and assessment<br>of ASD patients ages 16 months through<br>30 months. | The EarliPoint System device is indicated<br>as a tool to aid qualified clinicians in the<br>diagnosis and assessment of Autism<br>Spectrum Disorder (ASD) in children<br>ages 16 months through 30 months, who<br>are at risk based on concerns identified<br>by a parent, caregiver, or healthcare<br>provider. |
| Prescription Use | Yes | Same as predicate |
| Product Code and | QPF | Same as predicate |
| Regulation<br>Number | 882.1491 | Same as predicate |
| Device<br>Components | • Eye-tracking module captures the<br>patient visual response to social<br>information provided in the form of a<br>series of age-appropriate videos.<br>• Operator's module is used to initiate<br>and monitor the session remotely | Same as predicate |
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| Device<br>Characteristic | Predicate Device K230337<br>EarliPoint System | Subject Device<br>EarliPoint System | | |
|--------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------|-----------------------------------------------------------------------------------------------------------|-------------------|
| | WebPortal securely stores all patient information, analyzes the eye tracking data, and outputs the results. Users can retrieve the results directly from the web-portal. Software analyzes the eye-tracking data and provides a diagnosis for ASD. In addition, it also outputs 3 developmental delay indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments | | | |
| | ASD Diagnosis | | Use software algorithm to analyze the eye tracking data for ASD diagnosis ad assessment | Same as predicate |
| | Electrical Safety<br>Testing | | Meets electrical safety standards per: IEC 60601-1:2005/AMD1:2012/AMD2:2020 IEC 60601-1-2:2014/AMD1:2020 | Same as predicate |
| | Software | | Compliant to ISO 62304 | Same as predicate |
| | Clinical data | | Pivotal trials provide safety and effectiveness data. | Same as predicate |
| | Risk level of the<br>device | | Low risk device, non-invasive | Same as predicate |
## CONCLUSION
Both devices have the same intended use and technological characteristics. The clarifications made to the indications for use statement do not impact the safety and effectiveness of the device. The conclusions drawn from the nonclinical studies have not been impacted by this clarification in the indications for use statement. Hence, the subject device is substantially equivalent to the predicate device.
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.
