MedAI Verdict
Mental health

AI Mental Health

Lyssn

by Lyssn.io  ·  US

Last verified

Supervision + quality-metrics AI for therapist training.

At a glance

Pricing
Enterprise.
HIPAA
Not disclosed
SOC 2
Not disclosed
EHRs
—
Founded
—
HQ
US
On this page

Independent score  ·  By our public rubric

30/100Competitive
How it’s computed →
  • Regulatory & Compliance
    0/25

    No FDA clearance listed

  • Clinical Integration
    0/13

    No EHR integrations listed

  • Evidence Strength
    20/20

    5 peer-reviewed papers

  • Vendor & Market
    6/18

    Early-stage company

  • Sentiment & Transparency
    2.5/18.5

    Pricing on request, no public amounts

▸ Show all 11 dimensions

Regulatory & Compliance

  • FDA clearance0/12

    No FDA clearance listed

  • HIPAA / SOC2 / BAA0/13

    No public HIPAA/SOC2/BAA attestation

Clinical Integration

  • EHR integrations (count)0/7

    No EHR integrations listed

  • Top-3 EHR coverage (Epic / Oracle / Athena)0/4

    None of the top-3 EHRs covered

  • Bidirectional write-back0/2

    No bidirectional write-back documented

Evidence Strength

  • Peer-reviewed papers14/14

    5 peer-reviewed papers

  • RCT / meta-analysis / systematic review6/6

    2 RCT/Meta-Analysis/Systematic Review

Vendor & Market

  • Funding & adoption signal6/12

    Early-stage company

  • Years in market0/6

    Founded year not recorded

Sentiment & Transparency

  • Clinician sentiment (Reddit)0/14

    No clinician sentiment data available

  • Pricing transparency3/5

    Pricing on request, no public amounts

Scored October 15, 2026 · Public scoring method v1.1.0

Bottom line

Supervision + quality-metrics AI for therapist training.

Free tier available.

Editorial review  ·  By MedAI Verdict

Bottom line

A behavioral health agency, crisis line or training program that must measure session quality is the buyer for Lyssn. It is a Seattle company that uses AI to score recorded therapy and counseling sessions against evidence-based practice measures, and to run AI-scored training modules. Documentation is an optional extra, so an individual therapist looking for a note writer should look at a scribe such as Mentalyc or JotPsych. Pricing is quote only.

What is Lyssn and who sells it?

Lyssn.io, Inc. is incorporated in Washington and based in Seattle. It was founded in 2017. David Atkins has been CEO since July 2017, Zac Imel is founder and Chief Science Officer, and Michael Tanana is CTO. Crunchbase lists Atkins, Tanana, Tad Hirsch and Imel as founders. The vendor describes the team as "Ph.D-level clinical researchers and data scientists". PitchBook lists 33 employees. Other sources give a range of 11-50.

Funding figures disagree by source. CB Insights reports $8.42M total, with a last $3.2M convertible note. PitchBook reports $4.29M, with a latest $2.9M debt round in 2026. Tracxn reports $2M. The money is described as mostly government grants from NIMH, NIH and HHS, and no Series A or ownership change is listed.

The homepage says Lyssn offers "research-backed AI solutions to measure what matters in health & human services". It applies AI and natural language processing to help organizations implement and model fidelity to evidence-based practices.

What does Lyssn do well?

The product is narrower than a scribe, and it is documented on the vendor's pages.

Sessions are recorded or uploaded, transcribed and reviewed against "more than 75 clinically and externally validated measurements of quality" (vendor wording). Measures include empathy, active listening, collaboration, affirmations and client change language for Motivational Interviewing, plus CBT subscales such as agenda setting, guided discovery and homework.

Views exist for individual providers, teams and offices, and fidelity reporting is available for funders.

In the Learn and Practice area, AI-scored training modules give personalized feedback on evidence-based practice. The homepage news also lists a suicide prevention training program.

Optional AI Notes can generate a clinical summary in the organization's template.

Lyssn says it undergoes "regular external HIPAA and SOC 2 audits" and that data security attestation reports are "available upon request". It also says it is FERPA-compliant and uses encryption and two-factor authentication. The audit firm logo links to A-LIGN. Recordings are available for 90 days by default, then de-identified, or deleted on request, and data are de-identified before algorithm calibration. The customer is responsible for recording consent.

A clinical director who has to show a funder that counselors deliver Motivational Interviewing as designed is the use case Lyssn is built around.

Where does it fall short?

The vendor's evidence figures are inconsistent. The homepage says "17 years" of research, "4.5 million+" analyzed sessions and "65+" peer-reviewed publications. The quality-improvement page says 4.3 million sessions and "60+" publications. The accuracy percentages on that page are not readable as published.

A vendor-oriented summary reports 92% accuracy on a Motivational Interviewing metric, comparable to human raters, and that figure is not independently verified.

A physician-tools directory notes that feedback arrives after the session and so tends to be discussed in supervision, that separate tools are needed for documentation, and that implementation involves cultural change and lengthy IT security reviews.

The page does not name the dates or the framework scope of the audits. HITRUST and FDA status are not stated. A Business Associate Agreement is not stated explicitly, and no EHR integration is named.

What does Lyssn cost?

Quote only. The site shows no prices, directs buyers to contact sales, and gives no billing period.

How does Lyssn compare?

Mentalyc and JotPsych write therapy notes, and Wysa is a patient-side chatbot. Lyssn measures how a session was delivered.

On the web, CB Insights lists Eleos Health and Tali AI as Lyssn competitors. Eleos, Upheal and Mentalyc overlap partly with Lyssn, with documentation on one side and fidelity coding on the other. Comparison content from Mentalyc and Twofold is competitor marketing.

Lyssn wins where an organization needs measurement of practice quality and training at scale. It loses for a private practice that needs notes in the EHR by the end of the day, because documentation is an add-on and EHR integration is undocumented.

What does the evidence say?

Five papers are linked to Lyssn. The one titled as AI fidelity feedback is a 2022 article in BMC Health Services Research on enhancing the quality of cognitive behavioral therapy in community mental health (PMID 36127689). The other four are from 2024: a Clinical Psychology & Psychotherapy paper on identifying effective components of computer-assisted CBT (PMID 39625130), a Trials protocol for a CBT depression trial (PMID 39375728), a JMIR Formative Research evaluation of nurse training in suicide safety planning (PMID 39239987) and an Addiction Science & Clinical Practice paper on counseling quality in opioid treatment programs (PMID 38245783). Their titles do not show whether they evaluate Lyssn's software.

A paper list shows research activity around the product. It does not show that Lyssn's scores match human raters in your setting, so ask for the validation report behind the 75 measures.

Who is Lyssn for?

A county behavioral health agency that must report fidelity to a funder. A crisis line that wants to give counselors feedback on every call, not a sample. A training program for CBT or Motivational Interviewing that wants scored practice sessions for learners.

It is not for a solo therapist who wants a faster note, a practice that needs a documented EHR connector, or a buyer who needs a public price before a first call.

The verdict

Lyssn is a research-rooted quality and training platform for organizations, and its price and integrations are unclear. Request pricing, the audit attestation and the validation data behind the 75 measures before committing.

Editorial review last generated October 14, 2026. Synthesized from clinician sentiment, peer-reviewed coverage, and our editorial silo picks. Refined by hand where vendor facts change.

Pricing

What it costs

Free tier only, no paid plans publicly disclosed.

TierMonthlyAnnualNotes
Plan——Enterprise.

Source: vendor pricing page. Last checked October 14, 2026.

Peer-reviewed coverage

What the literature says

5 peer-reviewed studies indexed on PubMed evaluate Lyssn in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

Using Artificial Intelligence to Identify Effective Components of Computer-Assisted Cognitive Behavioural Therapy.
Coleman JJ, Owen J, Wright JH, et al.· Clin Psychol Psychother· 2024RCT
Although clinician-supported computer-assisted cognitive-behaviour therapy (CCBT) is well established as an effective treatment for depression and anxiety, less is known about the specific interventions used during coaching sessions that contribute to outcomes. The current study used artificial intelligence (AI) to identify specific components of clinician-supported CCBT and correlated those scores with therapy outcomes. Data from a randomized clinical trial comparing clinician-supported CCBT with treatment as usual in a primary care setting were utilized. Participants (n = 95)…
Protocol for a randomized controlled trial: exercise-priming of CBT for depression (the CBT+ trial).
Meyer JD, Kelly SJE, Gidley JM, et al.· Trials· 2024RCT
Depression is a leading cause of disability worldwide, and treatments could be more effective. Identifying methods to improve treatment success has the potential to reduce disease burden dramatically. Preparing or "priming" someone to respond more effectively to psychotherapy (e.g., cognitive behavioral therapy [CBT]) by preceding sessions with aerobic exercise, a powerful neurobiological activator, could enhance the success of the subsequently performed therapy. However, the success of this priming approach for increasing engagement of working mechanisms of psychotherapy (e.g., increased wor…
Improving the quality of counseling and clinical supervision in opioid treatment programs: how can technology help?
Peavy KM, Klipsch A, Soma CS, et al.· Addict Sci Clin Pract· 2024
The opioid epidemic has resulted in expanded substance use treatment services and strained the clinical workforce serving people with opioid use disorder. Focusing on evidence-based counseling practices like motivational interviewing may be of interest to counselors and their supervisors, but time-intensive adherence tasks like recording and feedback are aspirational in busy community-based opioid treatment programs. The need to improve and systematize clinical training and supervision might be addressed by the growing field of machine learning and natural language-based technology, which can…
Harnessing Innovative Technologies to Train Nurses in Suicide Safety Planning With Hospital Patients: Formative Acceptability Evaluation of an eLearning Continuing Education Training.
Darnell D, Pierson A, Tanana MJ, et al.· JMIR Form Res· 2024
Suicide is the 12th leading cause of death in the United States. Health care provider training is a top research priority identified by the National Action Alliance for Suicide Prevention; however, evidence-based approaches that target skill building are resource intensive and difficult to implement. Novel computer technologies harnessing artificial intelligence are now available, which hold promise for increasing the feasibility of providing trainees opportunities across a range of continuing education contexts to engage in skills practice with constructive feedback on performance. This pilo…
Enhancing the quality of cognitive behavioral therapy in community mental health through artificial intelligence generated fidelity feedback (Project AFFECT): a study protocol.
Creed TA, Salama L, Slevin R, et al.· BMC Health Serv Res· 2022
Each year, millions of Americans receive evidence-based psychotherapies (EBPs) like cognitive behavioral therapy (CBT) for the treatment of mental and behavioral health problems. Yet, at present, there is no scalable method for evaluating the quality of psychotherapy services, leaving EBP quality and effectiveness largely unmeasured and unknown. Project AFFECT will develop and evaluate an AI-based software system to automatically estimate CBT fidelity from a recording of a CBT session. Project AFFECT is an NIMH-funded research partnership between the Penn Collaborative for CBT and Implementat…

See all on PubMed