“Clinical validation and clinical safety are at the heart of everything we do. It is not a feature we added. It is the foundation we were built on.”

As part of the Venturebeam Venture Impact Score (VIS) Founder Series, we speak with founders building impact-driven companies across our platform. 

Today, we highlight HelloBetter, a digital mental health company developing clinically validated therapeutics and AI-based support tools.

We spoke with co-founder & CEO Hannes Klöpper on building safe, evidence-based mental health solutions at scale.

Q: With the introduction of HelloBetter’s AI companion Ello, how are you differentiating in an increasingly crowded digital mental health landscape? Specifically, what role does clinical validation play in its development and deployment?

Clinical validation and clinical safety are at the heart of everything we do at HelloBetter. It’s not a feature we added — it’s the foundation we were built on.

For ten years, we’ve been developing digital therapeutics (DiGAs) for conditions like panic, depression, burnout, insomnia, and chronic pain, etc. That work required us to meet some of the highest bars in digital health: 30+ randomised controlled trials, 150,000+ patients supported, prescribed by 1 in 4 GPs in Germany . To be able to distribute DiGAs in the first place, you have to demonstrate clinical relevance and show real results. That rigour is in our DNA — it’s the backbone of everything we do and the reason we’re where we are today.

So when we saw that AI companions were exploding — and that emotional support had become the #1 use case for ChatGPT in 2025 — we knew we had to be in this space. Not because it was trendy, but because as digital mental health experts, we had a responsibility to make sure this was built in a safe, ethical way. People were already discussing their mental health with AI, so we had to meet them where they are. Also it plays into our vision of meeting people way earlier – right now, people are waiting for 10 years until they seek professional help for their problems. Conversational AI can be a starting point of this journey and suitable to reduce it drastically, hopefully to weeks and months, not years.

That’s why we built Ello. And what differentiates it in an increasingly crowded landscape comes down to four things:

1. Clinical expertise is always in the room. As we develop Ello, there is always a clinical expert involved. Everyone working on the product has clinical expertise. This isn’t an engineering team that consulted a psychologist once — it’s psychologists, psychotherapists, and risk managers who are embedded in every step of product development, training, and quality evaluation .
2. Purpose-built psychological architecture. It doesn’t just tell you what you want to hear, it gently challenges unhelpful thought patterns, the way a real therapist would
3. Multi-layered safety with crisis detection for suicidal ideation and self-harm, a human-in-the-loop layer where users can connect directly with psychologists if they need to talk to a human. 
4. European-first, privacy by design. Ello is GDPR-native, hosted on the same EU servers as our CE-marked medical devices. That’s DiGA-level data privacy for a wellness product — a standard most competitors simply can’t offer.

We’ve also launched the ADAPT study to rigorously evaluate Ello’s outcomes. Not because we position Ello as a medical device — it’s a wellness companion — but because we believe that if you’re going to build AI for mental health, you owe it to your users to evaluate it properly. 

Q: As you expand into new markets, how do you ensure consistent, clinically validated outcomes across different healthcare systems and patient populations? What are the key challenges in maintaining that standard?

The “good” thing about Europe is that everything is very regulated. And while that can be seen as a barrier, for us it’s actually a strength — because when we enter a new market, we know exactly what we need to conform to. The regulatory frameworks give us a clear blueprint for what the product needs to deliver in order to be safe, effective, and distributable.

Our approach to each market entry:

Every new market gets a dedicated team that conducts a thorough analysis across two dimensions:

1. Market access — how do we reach patients? What are the reimbursement pathways? Who are the prescribers? What are the distribution channels? Each healthcare system has its own logic, and we map that out before we go in.
2. Product requirements — what needs to be in the product for it to be relevant, safe, and distributable in this specific country? This covers regulatory requirements, clinical evidence expectations, language and cultural adaptation, and local safety standards.

When needed, we run additional studies. Sometimes entering a new market means we need to conduct a new pilot study to test our digital therapeutic on a different patient population. We don’t assume that what works in Germany will automatically transfer to France or another market. We test it. We validate it. We do what it takes.

The key challenges in maintaining that standard:

• Regulatory fragmentation across Europe. Even within the EU, each country has its own nuances around digital health regulation, reimbursement, and certification. What qualifies in Germany’s DiGA framework doesn’t automatically transfer to France’s PECAN pathway or other national systems. Each requires specific preparation and adaptation.
• Different patient populations. The way people experience and express mental health challenges varies across cultures. A burnout programme that resonates in Germany may need to be adapted — not just translated — for a French or Southern European population. Our clinical teams evaluate this for every market entry.
• Scaling clinical expertise. Each market entry requires local clinical knowledge — understanding the healthcare system, the prescriber landscape, and the patient journey. Building and maintaining that expertise across multiple countries is an ongoing operational investment.

Q: What metrics do you consider most meaningful in demonstrating long-term impact on patient outcomes, beyond engagement or completion rates? How do you track and evidence sustained clinical improvement over time?

To evaluate the efficacy and main benefits of our therapy programmes, we conduct clinical evaluations both in a controlled environment (efficacy evaluations in randomised controlled clinical trials) as well as in routine care (real-world evidence).

To evaluate our programmes in routine care (real-world evidence), we regularly monitor our patient’s progress throughout the programme. Every two weeks, patients fill out validated questionnaires on their mental health status (symptom check). This allows us to evaluate real-world effectiveness in real-time.

We observe that the results of our real-world evidence outcomes are comparable to those of the RCTs and show a relevant reduction in symptoms in routine care as well. Evaluations are continuously conducted for all of our DiGAs.

Q: Your programmes are integrated into the healthcare system and reimbursed through insurance. How has this model influenced patient adoption, and how do you measure impact across patients, providers and payers?

How the model influences patient adoption:

As a DiGA provider, insurance reimbursement has been transformative for patient access. With 73 million publicly insured individuals in Germany able to access our programmes free of charge, we’ve eliminated the primary barrier to mental health care: cost. Patients can obtain a prescription from their doctor or apply directly with their insurance, removing financial concerns and significantly reducing wait times compared to traditional psychotherapy. This model has democratised access to evidence-based mental health interventions.

Measuring impact across stakeholders:

• Patients: We track clinical outcomes (symptom reduction using validated instruments like PHQ), treatment satisfaction, and adherence rates. Our real-world evidence studies show results comparable to RCTs.
• Providers: We monitor prescription rates, physician feedback, and professional acceptance.
• Payers: Impact is demonstrated through the DiGA regulatory framework, which includes the upcoming performance-based remuneration and ongoing real-world effectiveness measurement requirements (from Q3 2026 onwards). We will submit data to BfArM every six months on usage patterns, patient-reported satisfaction and health status. Reimbursement prices are negotiated with the GKV-Spitzenverband based on clinical evidence, and effectiveness data will be publicly available in the DiGA directory.