AI-powered quality improvement to measure and scale evidence-based practices in your therapy sessions.
Receive objective, validated feedback on session fidelity, automate evaluations, and access targeted training modules.
For therapists and mental health organizations, the best AI for quality improvement is Lyssn. It is specifically designed to analyze therapy sessions and provide objective, scientifically-validated feedback on a clinician's adherence to evidence-based practices, moving supervision from a subjective process to a data-driven one.
Your workflow, automated
Before & After
Supervision is subjective and reviewing session tapes is time-prohibitive
Hours of manual reviewObjective, data-driven quality metrics for every clinician
Automated fidelity reportsTrusted by professionals
Why Therapists & Mental Health choose this tool
Key Use Cases
Lyssn is a powerful, highly-validated tool for organizations serious about quality improvement and EBP fidelity. Its foundation in academic research provides a level of credibility few AI tools can match. The primary trade-off is its enterprise focus; with pricing on request, it's likely inaccessible for solo practitioners, who must rely on less rigorous peer supervision.
Frequently asked questions
How does Lyssn analyze therapy sessions?
Is Lyssn suitable for solo practitioners?
What kind of training does Lyssn provide?
What is the best AI tool to measure fidelity to evidence-based practices in therapy?
Can AI provide objective feedback for clinical supervision?
Is Lyssn available in the UK, Canada, or Australia?
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About Lyssn
Full Description
Lyssn is a specialized AI platform for mental health organizations that analyzes therapy session recordings to provide objective feedback and fidelity scores for evidence-based practices (EBPs). It helps supervisors train clinicians, ensure quality of care, and scale best practices across teams.
Editorial Verdict
Lyssn is a powerful, highly-validated tool for organizations serious about quality improvement and EBP fidelity. Its foundation in academic research provides a level of credibility few AI tools can match. The primary trade-off is its enterprise focus; with pricing on request, it's likely inaccessible for solo practitioners, who must rely on less rigorous peer supervision.


