Not as a metaphor. As a measurable, validated capability.
"I've spent 15 years studying how humans understand emotion.
First as a clinical psychologist - sitting across from people in crisis, learning to read what they weren't saying. The micro-expressions. The pauses. The words they chose when they were trying not to break down.
Then as an AI engineer - building systems that talk to millions of people, realizing that nobody was teaching these systems the thing that mattered most: empathy.
Here's what I saw: AI companies optimize for accuracy. For speed. For deflection rates and cost savings.
But nobody optimizes for care.
The result? Technically perfect AI that sounds like it's reading from a manual while your customer is having the worst day of their life.
I couldn't unsee it. I couldn't not build this.
EmpathyC is my answer to a question that's been following me for years: What if we measured emotional intelligence in AI the same way we measure it in humans?
Not through vibes. Not through engagement metrics. Through validated clinical psychology frameworks that we've used to assess human empathy for decades.
We built EmpathyC because AI is talking to your customers right now, and someone needs to make sure it gives a damn."
Bridging two worlds: Clinical psychology meets AI interpretability
Most AI monitoring tools are built by engineers who understand machine learning but not human emotion. Psychological tools are built by psychologists who understand empathy but not how to make AI systems measurable.
We're different. We bridge both worlds.
Clinical psychology isn't about reading minds - it's about recognizing patterns in language, tone, and behavior that signal emotional states.
It's about knowing when someone needs space vs. when they need intervention. It's about understanding that "I'm fine" can mean five different things depending on context.
Our founder has sat across from hundreds of people in crisis, learning to read what they weren't saying. That's not intuition - that's trained pattern recognition based on years of practice with validated assessment frameworks.
AI interpretability is about making black-box systems understandable. It's about taking a model that processes millions of parameters and explaining why it made a specific decision.
It's about measurable, auditable, debuggable behavior.
Our founder has built production AI systems used by millions, including crisis response platforms where "the model made a mistake" isn't acceptable. That's not just engineering - that's systems thinking under life-or-death constraints.
Psychological safety in AI isn't about sentiment scores or tone detection. It's clinical territory: crisis detection, boundary violations, harmful advice patterns. The same frameworks used to assess human psychological risk, now applied to conversational AI.
Medical ethics, the foundation we work from:
EmpathyC bridges clinical psychology and AI engineering to prevent AI-driven psychological harm:
6 validated safety metrics:
Proven methodology: During COVID, we built a psychological support platform for 320 frontline medical workers. Zero PTSD cases. From applying validated clinical frameworks to detect crisis signals before they escalated.
Clinical Psychologist → AI Engineer
The transition from therapy to AI wasn't random. It was the realization that everything learned about how humans process emotion, communicate under stress, and build trust could be encoded into measurable, interpretable systems that serve for good.
That's EmpathyC's unique advantage:
EmpathyC is what happens when someone who understands both worlds bridges the gap.
This mission is bigger than one person. If you're a psychologist who understands AI, an engineer who cares about emotional intelligence, or a researcher who believes technology should serve humanity - this might be for you.
We're not posting job openings. We're looking for people who can't not work on this problem.
If that's you, let's talk about what role you could play in teaching AI to care.
Reach out directly:
// Pattern recognition, not obfuscation
bWljaGFlbEBlbXBhdGh5Yy5jbw==Transparency requires engagement. If you're curious enough to decode this, you already understand how we work.
AI is about to talk to billions of people.
Customer support. Mental health triage. Education. Healthcare. Crisis hotlines.
If we don't teach these systems empathy now - measurable, validated, auditable empathy - we're going to hurt a lot of people.
Not because AI is evil. Because it's indifferent.
And indifference, at scale, is devastating.
We built EmpathyC because we refuse to live in a world where AI optimizes for efficiency while ignoring the human on the other side of the screen.
We're not trying to make AI "seem" empathetic. We're trying to make it care - in the only way a machine can: by measuring, learning, and improving its ability to recognize and respond to human emotion.
That's the mission. That's why this exists.
If you book a discovery call, you'll talk to Mike directly. Not a sales team. Not an account executive.
Just Mike.
Because we want to understand your problem before pitching a solution. That's the clinical psychology training talking—assessment before intervention.
If EmpathyC isn't the right fit, we'll tell you. If there's a better way to solve your problem, we'll point you there.
We're building this company the way therapy is practiced: evidence-based, transparent, and genuinely focused on helping.
We use validated clinical psychology frameworks, not vibes. We show you our methodology, our false positive rates, our evaluation criteria. Transparency is the product.
AI should augment human care, not replace it. We're building tools for CS teams who give a damn about their customers, not tools to eliminate those teams.
You talk to Mike, not a sales funnel. You get honest assessments, not pitches. You get a thinking partner, not a vendor.
We're building AI in public. AI community, open research, and founder-to-founder conversations. This technology is too important to build behind closed doors.
We're not here to sell you software or service. We're here to solve a problem we couldn't ignore.
If you're running conversational AI and you're worried about empathy failures, brand risk, or customer trust - let's talk.
30 minutes. Just you and Mike. No pitch deck. Just a conversation about whether EmpathyC is the right solution for your problem.
P.S. - If you're curious about the clinical psychology frameworks we use, or the technical architecture behind our empathy detection, or why we think AI safety starts with emotional intelligence - Mike loves talking about this stuff. Seriously. Book a call and ask him anything.