Live consultation transcription
AI-powered speech-to-text captures the clinical interview in real time. Segments attach to the assessment with timestamps. Encrypted at rest.
EIR is a clinical decision-support platform that combines automated EEG analysis with clinical information to support more informed psychiatric assessment and treatment planning.
Built with psychiatrists, for psychiatrists. We are currently running a small pilot programme — if you are a psychiatrist interested in adding objective neurophysiological data to your ADHD assessments, we would like to speak with you.
A short Muse EEG recording is combined with the patient's questionnaires and the transcribed clinical interview, then summarised by AI into a structured journal note the psychiatrist reviews and signs.
Alpha peak frequency, frontal lobe activation, beta/theta ratios — written as clinical prose, not raw numbers.
Self-report scoring and live consultation transcription folded into the same report. One coherent narrative.
Diagnostic considerations and concrete next-step recommendations. Editable, regeneratable, clinician-signed.
Example report below — patient identifiers anonymised. The treating clinician retains full editorial control over every word that goes into the patient record.
Generated journal note — Patient A, anonymised. Includes EEG summary, ASRS-v1.1, clinical interpretation and next-step recommendations.
~5 min eyes-open + eyes-closed Muse recording.
Quantitative EEG analysis with MNE-Python v5 — individualised bands, age-based norms.
Clinical journal note rendered in plain English.
Clinician reviews, edits if needed, signs and attaches.
Most psychiatric assessments still rely heavily on interviews, questionnaires, behavioural observations, and retrospective recollection. These are essential parts of assessment, but they also introduce variability between clinicians, clinics, and patient populations.
At the same time, demand for neurodevelopmental and mental health assessment has increased dramatically. ADHD pathways in particular are under significant pressure, with growing waiting lists and increasing complexity in differential diagnosis.
Historically, objective neurophysiological tools such as EEG have remained largely confined to academic research environments, neurology departments, and epilepsy services because they required specialist equipment, technical expertise, and complex interpretation.
EIR aims to make neurophysiological insights accessible within routine psychiatric care.
ADHD assessment represents one of the clearest examples of the pressures currently facing psychiatric services. Diagnostic pathways are often lengthy, highly subjective, and affected by variability in presentation across age, gender, and socioeconomic groups.
Historically, ADHD was significantly under-recognised, particularly in girls and women who often present differently from traditional male-centred diagnostic models. More recently, growing awareness and demand have placed enormous strain on assessment services.
EIR does not aim to replace clinical assessment or diagnose independently. Instead, the platform aims to provide clinicians with an additional layer of structured neurophysiological information that may support more informed and consistent decision-making.
ADHD is the first feasibility pathway for EIR. The broader platform vision extends across psychiatry and brain health.
The clinician conducts a routine assessment using the EIR platform alongside their usual consultation workflow.
The clinical interview is transcribed by EIR, and structured self-report questionnaires are completed within the platform. Both feed into the analysis.
A short EEG is recorded using an accessible headset. Signal processing and analysis are automated within EIR.
EIR generates a structured clinician-facing report drawing on the clinical interview, questionnaire data, and neurophysiological findings.
The clinician considers the report and recommendations and integrates findings into their own clinical decision-making process.
Neurophysiological insights recorded with EEG allow clinicians to observe patterns of brain activity related to attention, arousal, cognitive regulation, and emotional processing. This provides an objective layer of information that may support psychiatric assessment and treatment planning.
EEG is not diagnostic on its own. Traditionally, EEG acquisition and interpretation required specialist equipment and high technical expertise, which kept it out of routine psychiatric care. EIR automates the recording, processing, and interpretation pipeline so that neurophysiological insights become available within everyday clinical settings.
The platform combines EEG findings with questionnaires, clinical interviews, and patient information to generate a structured clinician-facing report. EIR does not make diagnoses independently. Final clinical decisions remain entirely with the treating clinician.
EIR makes EEG insights usable in psychiatry by automating recording, processing, and analysis. The platform does not rely on EEG alone; it combines neurophysiological findings with the clinical information gathered by the clinician, producing a comprehensive and structured report.
The system uses a consumer-grade EEG headset that is easy to obtain and easy to use. This makes the workflow practical, accessible, scalable, and straightforward to integrate into existing routine psychiatric care.
Frequency bands are calibrated to each patient rather than applying a single generic schema — improving the accuracy of band-power analysis.
Recorded patterns are interpreted against age-matched normative data, so findings are contextualised rather than read in isolation.
Signal quality is assessed automatically, so clinicians can rely on a consistent input to the analysis.
EEG acquisition and interpretation no longer require specialist neurophysiology expertise at the point of use.
Results are presented in a structured, narrative report rather than raw signal data.
Repeat recordings support treatment planning and follow-up over time.
Designed to sit alongside existing clinical documentation and assessment pathways.
Clinician-facing. UK-hosted. Single-tenant per organisation.
EIR is built as a full clinical workspace. ADHD-specific neurophysiology sits on top of an everyday patient journal that handles transcription, structured notes, medications, allergies and vital signs.
AI-powered speech-to-text captures the clinical interview in real time. Segments attach to the assessment with timestamps. Encrypted at rest.
SOAP-framework notes (Subjective / Objective / Assessment / Plan). Title, body, type and clinician attribution per entry. Edit and sign as you go.
Drug, dose, route, frequency, start/end. Severity-graded allergies with reaction and onset. Built for medication-safety checks at every visit.
BP, HR, temperature, SpO₂, weight/height with auto-BMI. ICD-10 coded problem list with onset and resolution dates.
AI-assisted letter drafting against your letterhead and signature block. Every generation logged for audit. Referrals and handovers in a fraction of the time.
AES-256 at rest on every PII field. WorkOS SSO. Full audit trail of every clinical action. UK data residency on Azure.
EEG and ADHD screening are added capabilities — the underlying journal still works as your day-to-day patient record.
EIR is a full clinical workspace. Patient overview, notes, vitals, medications, allergies, problems, conversations, recordings and a unified timeline — with EEG and ADHD assessment built in.
Patient record — 9 EHR tabs alongside structured neurophysiology
Every screen below is rendered from the EIR clinician application. Patient names anonymised; everything else is the real interface.
Patient identifiers are synthetic for marketing purposes. Pilot partners see their own clinical data behind enterprise SSO.
EIR brings together the tools clinicians already use, with structured neurophysiology added on top.
Automated band-power topographies, power spectral density and quality checks from a short consumer-grade recording.
Clinical interview captured live and attached to the assessment, so the report reads as a whole.
Clinician-facing summary combining EEG findings, interview and questionnaires in a single, readable view.
Standardised self-report responses captured and scored alongside the neurophysiological signal.
Medications, allergies, vital signs and clinical notes — all encrypted per field, all attributable.
Every action logged. Role-based access. WorkOS SSO for clinics. Data residency in the UK on Azure.
EIR has developed a fully functional MVP platform and is currently entering pilot testing with a small group of psychiatrists for clinical feedback.
The next phase focuses on structured feasibility trials, followed by clinical validation work — in the first instance focused on ADHD assessment. EIR is actively exploring academic and clinical collaboration partners in the UK and abroad.
Longer-term development includes broader validation studies across psychiatry and other brain-health applications.
EIR is not a replacement for clinical judgement. It is a tool designed to give psychiatrists access to a layer of information that has historically been unavailable in routine outpatient care.
We are currently piloting the platform with a small number of psychiatrists in the UK. Pilot partners provide clinical feedback that directly shapes how the platform develops. Academic co-authorship opportunities are available for those interested in contributing to peer-reviewed work.
The clinician view — EHR alongside neurophysiology
Our immediate focus is ADHD assessment in collaboration with psychiatrists. The directions listed below reflect longer-term research ambitions, not current product claims.
Psychiatry has historically had very few accessible biological tools available within routine clinical practice. EIR aims to help bridge this gap by making neurophysiological information usable in everyday workflows.
ADHD assessment is the first feasibility focus. The long-term vision extends across a wider set of clinical questions where neurophysiological insight may contribute to more consistent, evidence-informed care.
The goal is not simply technological innovation, but more equitable, consistent, and data-informed mental healthcare.
EIR aims to provide structured neurophysiological insights that support clinicians in making more informed decisions within routine psychiatric workflows.
EIR adds a structured neurophysiological layer to your existing workflow — it does not change the transcript and questionnaire data you already collect, presented as a structured clinician-facing report. There is no specialist equipment to manage beyond a consumer headset. There is no EEG training required. Reports are designed to be read, not decoded. If you are a psychiatrist interested in piloting EIR, write to Monica directly.
Email Dr Monica BerntsenPatients sign in with the Patient ID issued by their clinician, complete questionnaires, and complete the home EEG recording when prescribed.
Patient portalClinics evaluating new assessment workflows and research groups studying neurophysiology in routine psychiatric care. Pilot and partnership conversations are open.
Talk to usEIR TEC is small on purpose. Each founder owns a domain end-to-end, and answers their own email.
Practitioner Psychologist (HCPC PYL36943), PhD in Neuroscience from the University of Essex and a clinical degree from Adler University, Chicago. Specialises in ADHD and ASD assessment, qEEG, neurofeedback and brain stimulation. Runs an independent UK clinical practice.
EIR — named after the Norse goddess of healing — is registered as EIR TEC LTD in London (Companies House 15309722) with sister entity EIR TEC AS in Sandefjord, Norway (Foretaksregisteret 936 876 242).
EIR is designed from the ground up for the realities of clinical data — privacy, traceability and accountability.
Data Processor framework with signed DPA for every clinic.
Enterprise identity with role-based access and single-session enforcement.
Hosted in the UK on Azure with regional data residency.
Per-field encryption on patient identifiers, notes and clinical content.
Every clinical action and AI-assisted generation is logged and attributable.
Reports are reviewed and signed by the treating clinician. EIR does not diagnose.
EIR is currently in pilot testing. Clinical validation work is ongoing — see “Where EIR is today” above.
Sign in if you already have an account. If your clinic is interested in a pilot or feasibility collaboration, write to us.
For pilots, partnerships and press — pick whichever inbox fits. We answer our own email.