Ceribell

The hardware exists to feed the algorithm. A conventional EEG requires a technologist to place electrodes and a neurologist to read the tracing, which is exactly the bottleneck the company removes: Clarity is a machine learning algorithm interpreting EEG every ten seconds across all channels to produce a seizure burden estimate that a bedside clinician can act on without a neurologist present. The headband is a delivery mechanism for that interpretation, and the FDA clearances attach to the algorithm.

The system alerts rather than treats, and it is designed for a specific oversight gap: emergency departments and ICUs where 24/7 neurology EEG interpretation is unavailable. It provides continuous monitoring with instantaneous bedside alerts for suspected status epilepticus, plus a remote portal so a neurologist can access the real time tracing and guide treatment. That combination, an actionable bedside signal with an expert able to look at the underlying data remotely, is a well constructed oversight design for an acute setting. Buyers should still establish local protocol for who confirms an alert before anticonvulsant escalation.

The algorithm's operation is described with unusual specificity: a cloud based machine learning model interpreting all EEG channels every ten seconds, producing seizure burden defined as the amount of seizure activity in the prior five minute window, with pre annotations to support efficient human EEG interpretation. Defining the output metric explicitly rather than emitting an opaque risk score is good practice. Validation dataset sizes are disclosed for the regulatory submissions. Model architecture and per class performance figures are not published.

Evidence is anchored in regulatory validation at notable scale rather than published outcome trials. The pediatric clearance was supported by EEG data from more than 1,700 patients, which the company reports FDA data indicates was the largest validation dataset ever used for clearance of a seizure detection system, and the neonatal clearance was supported by data from more than 700 patients, described as the largest known neonatal validation set. Independent literature confirms deployment across academic and community hospitals in multiple states. What would move this to an A is published evidence that faster detection changes patient outcomes rather than detection performance alone.

No published PHI framework or data governance disclosure was located. The system is cloud based and processes continuous neurological data from critically ill patients, including neonates, with a remote clinician portal, so the data flow crosses the hospital boundary and warrants direct diligence.

No HIPAA or BAA statement was located in public materials, though business associate arrangements are structurally required for a cloud EEG platform deployed in US emergency departments and ICUs.

No SOC 2, HITRUST, or ISO 27001 attestation was located. As with other cleared device vendors, FDA clearance speaks to safety and effectiveness of the algorithm and says nothing about the vendor's information security posture.

A clear regulatory leader in its niche, with a progression that is worth reading as a pattern. The Ceribell System is FDA 510(k) cleared for detecting suspected seizure activity, and the Clarity algorithm received successive clearances extending its cleared population: adults, then patients aged 1 and older in April 2025, then preterm neonates and older in November 2025, making it the first and only AI point of care EEG cleared across the full age range from preterm newborns through adults. The company also reports the first FDA cleared instantaneous bedside alert for suspected status epilepticus. Expanding cleared indications incrementally with progressively larger validation datasets is the disciplined version of this pathway.

No formal governance framework was located, but the sequence of age specific clearances functions as de facto population validation: rather than claiming pediatric and neonatal performance from adult data, the company generated separate validation datasets and sought separate clearances for each population. That is the substance bias disclosure is meant to produce, applied to the demographic axis that matters most for EEG, where neonatal brain activity differs fundamentally from adult. No published analysis addresses other sources of variation.

No EHR integration, HL7, or FHIR capability was located. The workflow surface is the bedside device plus a remote neurologist portal rather than the chart, and medication annotation happens inside the Ceribell interface rather than flowing from the medication record.

Explicitly cloud based, with the Clarity algorithm described as a cloud hosted model and a portal providing remote real time access for neurologists. Beyond that characterization no tenancy, hosting, or data residency terms are published, which is a live question for a system operating in critical care.

No published pricing. As a public company the vendor discloses financial results in aggregate, which gives a buyer more visibility into business health than most vendors in this index provide, but nothing about per device, per use, or subscription cost is published.

Deliberately narrow clinically and unusually broad demographically. The clinical scope is electrographic seizure detection in acute care, specifically emergency departments and intensive care units including neonatal ICUs, where the company's own framing is that up to 90 percent of NICU seizures go undetected without monitoring. Against that single indication, the cleared population now spans preterm neonates through adults, which is wider than any comparable seizure detection system. Outpatient neurology and epilepsy monitoring units are not the target setting.