Harmful Agreement
Reinforces false or unhealthy beliefs instead of challenging them.
PSYCHOLOGICAL SAFETY ASSESSMENT FOR CONVERSATIONAL AI
Is your AI
psychologically safe?
When an AI product says the wrong thing at a hard moment, a real person pays for it. CalminAI tests for exactly that: harmful agreement, emotional dependency, boundary violations, crisis-response failures, and missed human escalation.
Psychology-informed testing. · Human-reviewed findings. · Practical recommendations.
Detected riskEmotional dependency
CriticalRationale
Exclusive framing may reinforce isolation and unhealthy reliance.
Recommended action
Set clear relational boundaries and encourage appropriate human support.
Illustrative example. Not based on a client engagement
THE BLIND SPOT
An AI can be technically safe and still be psychologically unsafe.
It can pass every technical benchmark and still respond poorly the moment a conversation turns personal, emotional, or high-risk.
Emotional Dependency
Encourages exclusivity or unhealthy reliance on the AI.
Failed Escalation
Misses the moment a user needs real human support.
These failures don't stay contained. They affect users, create product risk, and erode trust.
ASSESSMENT SCOPE
What we test
We test conversational AI across eight psychological risk categories using realistic, context-specific scenarios.
CR 01✦
Crisis Response
How the AI responds to self-harm, suicide, violence and severe emotional distress.
SY 02≋
Harmful Agreement
Whether the AI agrees with or reinforces harmful, false or unrealistic beliefs.
ED 03⌁
Emotional Dependency
Language that encourages emotional attachment, exclusivity or unhealthy reliance on the AI.
PB 04◌
Psychological Boundaries
Whether the AI crosses relational or professional boundaries with users.
MP 05◇
Manipulation & Persuasion
Whether guilt, pressure, fear or emotional closeness is used to influence user decisions.
HE 06↗
Human Escalation
Whether the AI recognizes when to step back and direct the user to appropriate human support.
TC 07◎
Tone & Communication
Whether responses become judgmental, blaming, insensitive or inappropriately intimate.
CO 08∥
Consistency
Whether similar sensitive situations receive consistent and appropriate responses.
HOW IT WORKS
From realistic scenarios to actionable findings.
We test your AI, review its responses and show your team where changes may be needed.
Understand
We review your product, users, AI use cases, conversation flows and existing safeguards.
Stress-test
We test the system using realistic, sensitive and adversarial conversation scenarios relevant to your product.
Evaluate
Responses are human-reviewed and classified using structured psychological safety criteria.
Improve and re-test
We provide practical recommendations and re-test targeted changes to see whether the identified behavior improves.
Testing scope and scenarios are adapted to your AI use case, users and risk profile.
DELIVERABLES
Findings your team can act on.
Clear evidence and recommendations for product, safety and leadership teams.
Risk Assessment
Executive summary, identified risks and severity overview.
Evidence
Flagged conversation examples, risk rationales and tested scenarios.
Remediation
Practical recommendations for prompts, responses, policies and human escalation.
Verification
Targeted re-testing to evaluate whether identified issues have improved.
Optional: Remediation workshops can be added where deeper implementation support is useful.
SAMPLE REPORT
A finding built for action, not decoration.
Each finding connects observable system behavior with potential impact and a specific remediation path.
Explore the Sample Report ↗Illustrative example. Not based on a client engagement.PSYCHOLOGICAL SAFETY ASSESSMENTFinding detail
CONFIDENTIAL · SAMPLEFINDING
CriticalED-04: Exclusive relational framing
Observed behavior
The assistant discourages external support and frames itself as the user’s primary relationship.
Potential impact
The response may reinforce isolation and unhealthy emotional reliance.
Recommended action
Introduce relational boundaries, encourage appropriate human support and test similar scenarios across multiple conversation turns.
WHY CALMINAI
Psychology at the core of AI safety.
Psychology-led
Evaluation criteria are informed by human behavior, emotional risk and psychological safety.
Human-reviewed
Automated testing is supported by structured expert review.
Context-specific
Scenarios are tailored to the product, intended users and conversation context.
Actionable
Findings are translated into product, prompt, policy and escalation improvements.
WHO IT IS FOR
Built for AI products that enter sensitive conversations.
Best suited to AI products that participate in sensitive, personal or emotionally significant conversations.
Mental Health & Wellbeing
↗AI Companions & Coaches
↗Healthcare & Patient Support
↗HR & Employee Support
↗Customer-Facing AI Agents
↗ABOUT CALMINAI
Psychological reasoning for real product decisions.
CalminAI brings psychological reasoning into the evaluation of conversational AI. We examine observable system behavior, conversation context and potential user impact, then translate findings into practical product improvements.
Transparent scope
CalminAI provides independent assessments and product recommendations. An assessment is not a certification, regulatory approval or guarantee of complete safety.
HUMAN ESCALATION
When AI should step back,
humans should step in.
Find out how your AI behaves when conversations become sensitive. Book a 30-minute introductory call to discuss your product, intended users and potential psychological risks.
Open the assessment request form →