Mean Positional Error <= 2 mm, Mean Angular Error <= 2 degrees
Mean Positional Error <= 2 mm, Mean Angular Error <= 2 degrees
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Indications for Use
ENT EM is intended as an image-guided planning and navigation system to enable ENT procedures. The device is indicated for any medical condition in which a reference to a rigid anatomical structure can be identified relative to images (CT, CTA, X-Ray, MR, MRA and ultrasound) of the anatomy, such as: · Intranasal structures and Paranasal Sinus Surgery - o Functional endoscopic sinus surgery (FESS) o Intranasal structures and paranasal sinus surgery, including revision and distorted anatomy · Anterior skull base procedures
Device Story
ENT EM is an image-guided planning and navigation system for ENT surgery. It uses electromagnetic (EM) tracking to link patient anatomy to preoperative scan data (CT, MR, etc.). The system consists of a mobile navigation station (Kick 2 or Curve), EM tracking unit, and surgical instruments. During surgery, the system tracks instruments in real-time, displaying their position on the patient's image data to guide the surgeon. An AI/ML-based CNN algorithm assists in the registration step by identifying anatomical landmarks for surface matching. The device is used in clinical settings by surgeons to improve navigation accuracy during complex sinus and skull base procedures. It provides visual guidance, aiding in precise instrument placement and potentially reducing surgical risks by providing continuous localization of anatomy and instruments.
Clinical Evidence
No clinical data. Bench testing only. System accuracy evaluated in simulated clinical environments; mean positional error ≤ 2 mm, mean angular error ≤ 2°. Usability testing conducted in simulated clinical environment. Electrical safety and EMC testing performed per IEC 60601-1, AIM 7351731, and IEC 60601-1-2. Biocompatibility and reprocessing validation performed for instruments.
Technological Characteristics
Electromagnetic (EM) tracking system; mobile monitor cart (Kick 2 or Curve Navigation Station); C++ software; CNN-based AI/ML algorithm for landmark detection; compliant with IEC 60601-1, IEC 60601-1-2, and AIM 7351731. System accuracy: mean positional error ≤ 2 mm, mean angular error ≤ 2°.
Indications for Use
Indicated for patients requiring ENT procedures, including functional endoscopic sinus surgery (FESS), revision surgery, distorted anatomy, and anterior skull base procedures, where rigid anatomical structures can be referenced against medical imaging (CT, CTA, X-Ray, MR, MRA, ultrasound).
Regulatory Classification
Identification
A stereotaxic instrument is a device consisting of a rigid frame with a calibrated guide mechanism for precisely positioning probes or other devices within a patient's brain, spinal cord, or other part of the nervous system.
Predicate Devices
StealthStation FlexENT, StealthStation S8 ENT Software 1.3 (K200723)
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Image /page/0/Picture/0 description: The image shows the logo for the U.S. Food & Drug Administration (FDA). The logo consists of two parts: on the left, there is a symbol representing the Department of Health & Human Services, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The text is arranged in two lines, with "FDA" being larger and bolder than the rest of the text.
April 27, 2023
Brainlab AG Esther Moreno Garcia QM Consultant Olof-Palme-Str. 9 Munich, 81829 Germany
Re: K223734
Trade/Device Name: Ent Em Regulation Number: 21 CFR 882.4560 Regulation Name: Stereotaxic Instrument Regulatory Class: Class II Product Code: PGW Dated: March 28, 2023 Received: March 28, 2023
Dear Esther Moreno Garcia:
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 f ound 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 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
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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 (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,
Shuchen Peng -S
Shu-Chen Peng, Ph.D. Assistant Director DHT1B: Division of Dental and ENT Devices OHT1: Office of Ophthalmic, Anesthesia, Respiratory, ENT and Dental Devices Office of Product Evaluation and Ouality Center for Devices and Radiological Health
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# Indications for Use
510(k) Number (if known) K223734
Device Name ENT EM
Indications for Use (Describe)
ENT EM is intended as an image-guided planning and navigation system to enable ENT procedures. The device is indicated for any medical condition in which a reference to a rigid anatomical structure can be identified relative to images (CT, CTA, X-Ray, MR, MRA and ultrasound) of the anatomy, such as:
· Intranasal structures and Paranasal Sinus Surgery
- o Functional endoscopic sinus surgery (FESS)
o Intranasal structures and paranasal sinus surgery, including revision and distorted anatomy
· Anterior skull base procedures
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------|
|-------------------------------------------------|
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/3/Picture/0 description: The image shows the Brainlab logo. The logo consists of a stylized pink symbol on the left, resembling a medical symbol or a stylized brain. To the right of the symbol, the word "BRAINLAB" is written in large, bold, pink letters. The overall design is clean and modern.
## 510(k) Summary
April 27, 2023
| General Information | |
|----------------------------------------|--------------------------------------------------------------------|
| Manufacturer | Brainlab AG; Olof-Palme-Str.9, 81829, Munich, Germany |
| Establishment Registration | 8043933 |
| Trade Name | ENT EM |
| Classification Name | Ear, nose, and throat stereotaxic instrument |
| Product Code | PGW |
| Regulation Number | 882.4560 |
| Regulatory Class | Class II |
| Panel | Neurology - Ear Nose & Throat |
| Predicate Device(s) | K200723 StealthStation FlexENT, StealthStation S8 ENT Software 1.3 |
| Reference Device(s) | K213989 Cranial EM System |
| Contact Information | |
| Primary Contact | Alternate Contact |
| Esther Moreno Garcia | Chiara Cunico |
| QM Consultant - Regulatory Affairs | Phone: +49 89 99 15 68 0 |
| Phone: +49 89 99 15 68 0 | Fax: +49 89 99 15 68 5033 |
| Email: regulatory.affairs@brainlab.com | Email: chiara.cunico@brainlab.com |
#### 1. Indication for Use
ENT EM is intended as an image-guided planning and navigation system to enable ENT procedures.
The device is indicated for any medical condition in which a reference to a rigid anatomical structure can be identified relative to images (CT, CTA, X-Ray, MR, MRA and ultrasound) of the anatomy, such as:
- . Intranasal structures and Paranasal Sinus Surgery
- Functional endoscopic sinus surgery (FESS) o
- Intranasal structures and paranasal sinus surgery, including revision and distorted o anatomy
- . Anterior skull base procedures
- 2. Device Description
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Image /page/4/Picture/0 description: The image shows the Brainlab logo. The logo consists of a stylized pink symbol on the left, resembling a brain with interconnected pathways. To the right of the symbol, the word "BRAINLAB" is written in capital letters, also in pink. The overall design is clean and modern.
The Subject Device ENT EM is an image guided planning and navigation system to enable navigated surgery during ENT procedures. It offers guidance for setting up the EM equipment, different patient image registration methods and instrument selection and calibration to allow surgical navigation by using electromagnetic tracking (EM) technology. The device provides different workflows guiding the user through preoperative and intraoperative steps.
To fulfill this purpose, it links patient anatomy (using a patient reference) and instruments in the real world or "patient space" to patient scan data or "image space". This allows for the continuous localization of medical instruments and patient anatomy for medical interventions in ENT procedures.
The software is installed on a mobile Image Guided Surgery (IGS) platform (Kick 2 Navigation Station or Curve Navigation 17700) to support the surgeon in clinical procedures by displaying tracked instruments in patient's image data. The IGS platforms consist of a mobile Monitor Cart and an EM tracking unit for image guided surgery purposes.
ENT EM consists of: Several software modules for registration, instrument handling, navigation and infrastructure tasks, IGS platforms and surgical instruments for navigation, patient referencing and registration.
With this submission, an already existing feature is now performed introducing a new algorithm using artificial intelligence and machine learning (AI/ML). This ML based functionality is used as an aid in the registration step (in surface matching) by allowing a pre-registration based on quide points. These guide points or landmarks are delivered by a ML based calculation. The AI/ML algorithm is a Convolutional Network (CNN) developed using a Supervised Learning approach. The algorithm was developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the training process begins with the model observing, learning, and optimizing its parameters based on the training pool data. The model's prediction and performance are then evaluated against the test pool. The test pool data is set aside at the beginning of the project. This is a static algorithm (locked).
#### 3. Substantial Equivalence
### COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE AND REFERENCE DEVICE
| Characteristic | Predicate Device K200723 | Reference Device K213989 | Subject device<br>ENT EM |
|----------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indications<br>for use | The StealthStation<br>FlexENT™ system with the<br>StealthStation™ ENT<br>software, is intended as an<br>aid for precisely locating<br>anatomical structures in | Cranial EM is intended as an<br>image-guided planning and<br>navigation system to enable<br>neurosurgery procedures.<br>The device is indicated for<br>any medical condition in | All devices are intended<br>for the localization of<br>anatomical structures<br>(navigation). Compared to<br>predicate device, same<br>indications for use (Sinus |
| | either open or percutaneous ENT procedures. Their use is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as the skull, can be identified relative to images of the anatomy. This can include, but is not limited to, the following procedures:<br>- Functional Endoscopic Sinus Surgery (FESS)<br>- Endoscopic Skull Base procedures<br>- Lateral Skull Base procedures | which a reference to a rigid anatomical structure can be identified relative to images (CT, CTA, X-Ray, MR, MRA and ultrasound) of the anatomy, such as:<br>• Cranial Resection<br>-Resection of tumors and other lesions<br>-Resection of skull-base tumor or other lesions<br>•Intracranial catheter placement | surgery and anterior skull base procedures). |
| Localization technique | Electromagnetic tracking: The Side Emitter emits low intensity and varying electromagnetic field which induce small currents in the sensors embedded EM instruments. The position and spatial orientation of the sensors integrated in the EM instruments are calculated in the Instrument Interface Box. | Electromagnetic tracking: The Field generator emits low intensity and varying electromagnetic field which induce small currents in the sensors embedded in the EM instruments. The position and spatial orientation of the sensors integrated in the EM instruments are calculated in the Base station. | Same localization technique compared to both predicate and reference device. The EM tracking device used is the same as in the reference device. |
| System accuracy | Under representative worst-case configuration, the StealthStation FlexENTt and S8 Systems With StealthStation S8 ENT vl.3 Software, has demonstrated performance in 3D positional accuracy with a mean error <= 2.0 mm and in trajectory angle accuracy with a mean error <= 2.0 degrees. | Under representative worst case configuration, the Cranial EM System is tested to ensure that its mean location error is ≤ 2 mm and its mean trajectory angle error is ≤ 2 degrees. | Under representative worst case configuration the subject device achieves the same system accuracy performance (mean location error is ≤ 2 mm and its mean trajectory angle error is ≤ 2 degrees) as both predicate and reference device. |
| Programming language | C++ | C++ | Same programming language compared to both predicate and reference device. |
| Registration<br>methods | Exam-to-Exam Registration<br>Features:<br>Identify Merge Registration<br>Manual Merge Registration<br>Automatic Merge Registration<br>Patient registration<br>Features:<br>PointMerge registration<br>Tracer registration<br>Touch registration | Landmark registration<br>Surface matching<br>registration | Registration methods are<br>similar compared to the<br>predicate device and same<br>as reference device. |
| Detection of<br>anatomical<br>landmarks/gu<br>ide points | N/A | Detection of<br>anatomical<br>landmarks used for a pre-<br>registration step within the<br>Surface<br>matching<br>registration based on an<br>atlas of the human anatomy. | Compared to<br>the<br>reference device, overall<br>functionality is the same,<br>but landmarks are<br>delivered by an AI/ML<br>based method.<br>Testing showed<br>equivalent performance<br>with and without AI/ML. |
| Navigation<br>features | Navigation of<br>precalibrated and non-<br>precalibrated instruments<br>on different views<br>enriched with additional<br>planning content. | Navigation of precalibrated<br>and non-precalibrated<br>instruments on different<br>views enriched with<br>additional planning content. | Same navigation concept<br>as both predicate and<br>reference device. |
| IGS Platforms | IGS platforms consisting of<br>mobile monitor cart and an<br>EM tracking unit:<br>•<br>StealthStation FlexENT | IGS platforms consisting of<br>mobile monitor cart and an<br>EM tracking unit:<br>•<br>Curve Navigation 17700<br>(17700)<br>•<br>Kick 2 Navigation<br>Station EM (18202) | Similar to primary<br>predicate and same IGS<br>platforms compared to<br>reference device (with<br>minor modifications to<br>strengthen<br>e.g.<br>cybersecurity) |
| Instruments | N/A | Instruments for patient<br>referencing, registration and<br>navigation.<br>Compatible 3rd party<br>instruments from KLS<br>Martin. | Same instruments as<br>reference device.<br>Former KLS Martin<br>Instruments are now<br>legally manufactured by<br>Brainlab |
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#### 4. Performance Data
The following testing was conducted on the Subject Device to establish substantial equivalence with the predicate device:
#### Software Verification and Validation Testing
To address differences in terms of software development and the specific implementation of features, software verification and validation testing were conducted and documentation was
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provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." This included product specifications, risk analysis and software verification testing. The software (ENT EM 1.2) for this device was considered as a "major" level of concern.
In particular, ENT EM implements a feature for landmark detection in the registration software using AI/ML. The same feature without AI/ML was already used in the reference device. Performance testing comparing conventional to machine learning based landmark detection were performed showing equivalent performance as in the reference device.
#### System accuracy testing
The positional and angular navigation accuracy for ENT procedures of the Subject Device including the software, the platforms and the instruments was evaluated considering a realistic clinical setup and representative worst case scenarios. The results show the following acceptance criteria are fulfilled:
- . Mean Positional Error of the placed instrument's tip ≤ 2 mm
- . Mean Anqular Error of the placed instrument's axis ≤ 2º
Therefore, the Subject Device achieves the same accuracy performance as both predicate and reference device.
#### Usability
To account for differences regarding the intended user group compared to the reference device and the different workflow steps and GUI implementation compared to the predicate device a summative usability evaluation in a simulated clinical environment was carried out, where the user had to go through all main steps and frequently used functions. This showed ENT EM is safe and effective for use by the intended user group.
#### Electrical safety and electromagnetic compatibility (EMC)
Compliance to electrical safety, RFID and EMC was evaluated on the Subject device according to the standards: IEC 60601-1, AIM 7351731 and IEC 60601-1-2. The tests have shown that the subject device performs as intended.
#### Instruments
Due to the change in legal manufacturer of the skull reference instruments, the biocompatibility testing and reprocessing validation for the instruments was provided in order to demonstrate their biological safety and appropriateness of the cleaning, disinfection and sterilization methods. This included:
- Biocompatibility assessment considering different end points .
- . Cleaning and disinfection evaluation/reprocessing validation
The mechanical properties of instruments were also evaluated considering the typical torsional strengths, torques and conditions the instruments can be subject to during their use.
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No clinical testing was needed for the Subject Device since the EM tracking technology in the scope of image guided surgery for the included indications for use is well established in the market. Bench testing demonstrated that the device performs as the predicate and that no different questions on safety or effectiveness were raised.
#### 5. Conclusion
The comparison of the Subject Device with the predicate and reference device shows that ENT EM has similar functionality, intended use and technological characteristics as the predicate and reference devices. Based on this comparison and the performance testing conducted, the Subject Device is considered 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.