Mental Health Data Annotation Services
Training data for the mental health AI you're actually building. Therapy transcripts, mood classification, crisis signal detection, cognitive distortion labeling, and empathic response scoring — annotated by trained mental health specialists under licensed clinician adjudication, with the trauma-informed protocols mental health AI demands.
Mental Health AI Is Different. The Annotation Has to Match.
Mental health AI projects fail in the same spot, over and over: training data labeled by people who do not understand the clinical or cultural stakes. A therapy chatbot trained on data where "I'm fine" was labeled positive sentiment will miss the most important users. A crisis detection model trained without clinician-adjudicated labels misses subtle ideation. A CBT chatbot trained on translated English cognitive distortions feels foreign to non-English users at their most vulnerable moments.
AI Taggers operates a dedicated mental health annotation pipeline. Annotators have clinical psychology, peer support, or licensed counselling backgrounds. Crisis-tier work is reviewed by licensed clinicians with adjudication. Annotator wellbeing is treated as a first-class concern — rotation limits, decompression sessions, and EAP access for the people doing the work. Trauma-informed guidelines are the default, not an add-on.
For broader medical AI see clinical expert annotation. For Arabic mental health AI (a real and growing niche in Saudi Vision 2030 healthcare) see Saudi annotation paired with this service.
Annotation Tasks for Mental Health AI
From mood classification to clinician-adjudicated crisis detection — the full stack mental health AI needs.
Therapy Transcript Annotation
Turn-level labeling of therapy session transcripts: speaker identification, therapeutic technique tagging (open question, reflection, summary, validation), emotional content classification, and session-quality scoring against frameworks like MITI or PCQS.
Mood & Affect Classification
Sentiment beyond positive/negative — discrete emotion labeling (sadness, anxiety, anger, shame, hopelessness), valence-arousal continuous labeling, and clinically-validated mood scaling for PHQ-9 / GAD-7 / DASS-21 correlation.
Crisis & Suicidal Ideation Detection
High-stakes annotation for crisis triage AI. Suicidal ideation indicators, self-harm signals, risk severity grading, and protective factor tagging. Clinician-reviewed with dual annotation and adjudication on every record.
Cognitive Distortion Labeling
CBT-aligned tagging of cognitive distortions — Burns' 10, Beck's 6, or custom taxonomies. Trained against established psychotherapy literature for clinically-credible CBT chatbot training data.
Empathic Response Scoring
Rate AI-generated or human therapist responses on empathic accuracy, validation quality, therapeutic alliance, and clinical appropriateness. Used for RLHF on therapy chatbots and therapist training simulators.
Clinical Note & EHR Annotation
Mental health-specific EHR annotation: diagnosis extraction (DSM-5-TR / ICD-11), medication and dose tagging, psychometric score capture, treatment plan structured extraction, and discharge summary processing.
Who We Build Training Data For
Eight use cases drive most mental health AI annotation demand right now.
Therapy chatbots
Woebot-style and Wysa-style conversational mental health AI. Need empathic response training data, crisis detection, and CBT-aligned intervention labeling.
Crisis hotline triage AI
Suicide and crisis line text/voice triage. Highest-stakes annotation we perform. Requires clinician review and adjudication.
Mood tracking apps
Journal-entry and diary annotation for mood prediction, episode forecasting, and personalised intervention recommendation.
CBT and DBT digital therapeutics
FDA-track digital therapeutics need training data that respects evidence-based therapy frameworks. We follow your clinical advisor's protocol exactly.
Therapist training simulators
AI-powered standardised patients for trainee therapists. Need annotated patient-presentation variation, supervisor feedback rubrics, and intervention quality scoring.
Mental health screening tools
AI-augmented PHQ-9, GAD-7, PSS, DASS-21 screening — requires annotated correlation between free-text responses and validated screener scores.
Workplace wellbeing analytics
Anonymised employee survey and sentiment analysis for organisational mental health programs. Privacy-first annotation workflows.
Mental health LLM fine-tuning
Specialist Arabic, Spanish, French and English mental health LLM training data for region-specific products. Cultural idioms of distress respected.
Eight Safeguards That Make Us Different
Mental health annotation is high-stakes work. These controls are non-negotiable on every project.
Mental Health AI Training Service Pricing
Transparent indicative pricing by task. Final quote within 24 hours after scoping. Volume discounts 15-35% above 50K records.
| Task | Indicative Price | Unit |
|---|---|---|
| Mood / sentiment classification | $0.15 - $0.40 | per record |
| Cognitive distortion labeling (CBT) | $2.00 - $8.00 | per record |
| Therapy transcript turn labeling | $1.50 - $5.00 | per turn |
| Empathic response scoring | $2.00 - $6.00 | per response pair |
| Crisis / suicidal ideation detection | $4.00 - $12.00 | per record |
| Clinical note / EHR extraction | $2.50 - $9.00 | per note |
| PHQ-9 / GAD-7 correlation annotation | $1.00 - $4.00 | per response |
Crisis-tier tasks priced higher reflecting clinician adjudication and annotator wellbeing protocols. Full pricing page →
The Consent Question Most Vendors Avoid
Patient consent to therapy is not patient consent to AI training. This is the single highest-risk issue in mental health AI.
If your training data was collected without explicit AI-training consent, repurposing it can expose you to clinical-ethics complaints, regulatory enforcement, and reputational damage that no model performance gain justifies. We will not annotate data we suspect lacks appropriate consent.
We work with you to identify the cleanest path forward — synthetic data generation, retrospective re-consent campaigns, clinician-generated training data, or annotation of explicitly-consented research cohorts. If you're unsure whether your data is usable, ask us in the scoping call before sending anything. We'll tell you honestly.
Mental Health Annotation FAQ
What does mental health data annotation cost?▼
Who actually does the annotation?▼
Are you HIPAA compliant?▼
How do you handle annotator wellbeing for crisis work?▼
What cognitive distortion taxonomy do you use?▼
Can you handle multilingual mental health annotation?▼
Talk to our mental health annotation lead
Send a 25-50 record pilot brief. We'll match the task to clinically-credentialed annotators and return labeled samples within 72 hours under NDA. No commitment.