Manifesto

The Hidden Crisis

No doctor ever went to school to learn about revenue cycle management, billing workflows, or typing notes mid-visit. They became doctors because they wanted to help people. Yet today, they spend hours every day documenting - and it's not just one note they're writing!

Every single clinical note has to work for three completely different audiences: the care team needs to understand the medical reasoning, the billing department needs it coded properly for insurance, and patients want something they can actually read in their online portals.

Think about that for a second - we're asking some of the most highly trained professionals in the world to be technical writers for three different readers at once. The impact goes beyond just physician frustration.

Poor documentation means missed revenue from undercoding, high turnover from burned-out staff, and lost opportunities for quality improvement and research because the data simply isn't there in a usable format.

The mathematics are brutal too:

•50% of physician time spent on non-patient tasks

•63% of clinicians cite documentation burden as primary burnout driver

•€30-50k annual revenue leakage per physician from undercoding

•15-25% higher staff turnover in documentation-heavy specialties

Healthcare Is About Conversations

Our conviction is that healthcare is about conversations. Every word between doctors and patients, between care teams, and with insurers is the raw material of care.

And a lot more: the patient's medical history, how the clinic handles billing, what the insurance company requires, the specific combination of symptoms and medications that make each case unique. All of that context should be working for the doctor!

That's what we're building: a system that captures conversations wherever they happen (in-person, phone, video), structures them, and automatically produces the three outputs that matter - clinical, financial, and patient-facing notes. And we deliver them straight to where they belong: into the EHR, into billing systems, into patient portals.

When Technology Catches Up

Three simultaneous breakthroughs have converged to make ambient clinical documentation not just feasible, but inevitable:

Speech recognition reaches clinical accuracy: Modern speech recognition models achieve >95% accuracy on medical terminology. Whisper-based systems, fine-tuned on clinical vocabularies, now handle complex drug names, anatomical terms, and procedure codes with precision matching human transcriptionists.

Medical reasoning: Instruction-tuned models can now generate clinically appropriate, structured documentation that maintains medical accuracy while adapting to specialty-specific templates and coding requirements.

Health APIs finally opening up: HL7/FHIR adoption is accelerating across Europe. EHR vendors are exposing integration pathways that enable structured data insertion - not just text notes, but coded diagnoses, procedures, and billing information directly into appropriate fields.

European data sovereignty: Privacy regulations and data residency requirements are creating competitive moats for European solutions that can operate on your infrastructure or private cloud.

This constellation creates a once-in-a-generation opportunity to reconstruct healthcare's data infrastructure.

The Point of No Return

Early reactions make it clear: physicians find it not just useful, but life-changing!

It really is hard to go back, and, from first principles, it makes no sense to lose spoken and written context just to force doctors to manually re-enter it from memory while typing!

We meet them where they already are: in their EHRs, their dot phrases, their communication platforms, their existing workflows they've perfected over years.

It really comes down to building something with doctors and partners, for doctors, so they can feel like healers again instead of data entry clerks.

Much of the foundation is already live and in use - we've built and shipped a cross-platform system that doctors can use today.

•Cross-platform availability — Mena runs on Web, iOS, Android, macOS, and Windows. Clinicians can document wherever they practice: in clinic, hospital, or on the go.

•Fast documentation — With two taps (record → stop), a structured note generates in under 30 seconds. Refinements take less than 2 minutes, and regenerations ~5 seconds.

•Precision Mode™ — Custom templates are already broken down into semantic sections and validated. Doctors using our current version can lock notes into their preferred format, seeing outputs they can trust without starting from scratch.

•Voice and AI edits — Beyond initial generation, clinicians can edit hands-free ("add chest pain under history") or through AI chat-style commands ("make this summary patient-friendly"). Both are live today.

•Automated coding — ICD-10 and procedure codes are inserted inline with notes, ensuring revenue capture.

•Integration pathways — Mena is HL7/FHIR-ready, with a second EHR integration already underway. For non-API systems, our Smart Paste technology reliably fills structured fields.

In short: the core loop already works. Doctors record → Mena generates → trusted notes and codes appear → ready for transfer into EHR. Every week, we refine templates, accuracy, and integrations based on real clinician feedback.

Precision Mode™

Most ambient scribing solutions treat documentation as a text generation problem, throwing medical conversations at large language models and hoping for clinically acceptable text.

We realized this was fundamentally wrong. Clinical documentation isn't creative writing - it's structured data transformation that demands deterministic, repeatable results.

Precision Mode™ emerged from this insight. Rather than generating "good enough" prose, we built a deterministic engine that transforms conversational audio into structured, templated output with clinical-grade reliability. Think of it as the difference between asking AI to write a poem versus asking it to fill a database - the requirements for precision, structure, and repeatability are entirely different.

This creates something physicians have never experienced with AI tools: documentation they can trust.

The multi-modal input processing pipeline flows from raw audio through Whisper ASR (fine-tuned for medical terminology) to medical NER to semantic parsing to template filling. But the real magic happens in the contextual enrichment layer.

Vision

The ambient scribing and automatic coding we've built is just the beginning.

We're working on deeper integrations with EHRs that plug directly into the note templates doctors already use, and we're developing an AI reasoning system that will become the knowledge backbone for health systems across Europe, together.

The ultimate goal is a comprehensive platform that understands all data - both new and historical, reduces mental overhead, and gives doctors real-time or on-demand support for better decisions.

It's also pretty inevitable: just like nobody takes meeting notes by hand anymore and programmers don't write every line of code from scratch, in five years every clinician will have an AI scribe.

Deep Integrations

The most profound transformation in health technology doesn't happen when new systems replace old ones, but when the right partners collaborate to rebuild the foundation itself.

This is the story of what becomes possible when AI medical scribes integrate deeply with EHR and other systems that define current clinical workflows.

Real-time context awareness becomes possible when the AI system has bidirectional access to patient data, medication histories, and care team communication. The ambient intelligence doesn't just transcribe conversations - it understands clinical context, suggests relevant diagnostic codes based on documented findings, and flags potential care gaps or drug interactions as they naturally arise in conversation.

Template synchronization ensures AI-generated documentation exactly matches the structured note formats that doctors have perfected over years. Rather than forcing adaptation to new systems, the AI learns and replicates the clinical reasoning patterns and documentation preferences that make each doctor most effective.

Quality assurance improves dramatically when the AI system can validate its outputs against the EHR's built-in clinical decision support rules, drug databases, and specialty-specific guidelines. Every generated note meets not just grammatical standards, but clinical and regulatory compliance requirements.

But here's the architectural insight: the structured data already exists.

Beyond Documentation: The Context Layer Vision

Beyond fast and reliable transcription and templates, we're building Europe's first contextual reasoning engine for healthcare - a system that maintains continuous understanding of patient context, clinical workflows, and billing requirements.

Ambient scribing is the entry point to a larger transformation. Every structured clinical note becomes fuel for:

Automated Revenue Optimization
Zero-touch billing: Every documented procedure, diagnosis, and service automatically coded and optimized. Revenue leakage becomes impossible when AI captures every billable moment with clinical context.

Real-time Clinical Decision Support
Contextual intelligence: Analysis of patient history, current symptoms, and evidence-based protocols to surface diagnostic considerations, drug interactions, and treatment options - not replacing clinical judgment, but augmenting it with comprehensive data.

Population Health Analytics
Aggregated clinical intelligence: Structured data across patient populations enables quality metrics, outcome predictions, and research opportunities impossible with unstructured documentation.

European Health Infrastructure
The knowledge backbone: Standardized data that enables research collaboration, outcome comparisons, and evidence generation across European health networks.

Most healthcare AI solutions sit at the application layer. We're targeting a bigger picture - the context layer that captures, structures, and distributes clinical intelligence across European health systems - including your existing EHR and other vendors.

The Physician Experience

Physicians who experience deep EHR-AI integration describe it as finally working with technology that understands healthcare instead of fighting systems designed by people who've never seen a patient.

Cognitive load reduction is immediate and profound. Instead of splitting attention between patient care and data entry, doctors can focus entirely on clinical decision-making while trusting that their reasoning and decisions are being captured accurately and completely. The mental fatigue that comes from knowing you'll spend the next hour recreating conversations from memory simply disappears.

Documentation becomes predictive rather than reactive. As clinical reasoning unfolds during patient encounters, relevant templates and coding suggestions appear contextually, guided by the patient's specific history and current presentation. The system learns from each doctor's decision patterns and becomes increasingly helpful over time.

Care coordination improves naturally when every patient interaction generates structured, immediately accessible data that care team members can review, understand, and build upon. The informal knowledge that usually exists only in individual physician memories becomes part of the permanent, searchable patient record.

The Inevitable Future

Just as software development transformed from manual coding to AI-assisted development, clinical documentation will evolve from manual note-taking to ambient intelligence. The question isn't whether this transformation happens - but who builds the infrastructure that enables it.

The technical foundations are established. Speech recognition has reached clinical accuracy. Language models understand medical reasoning. Health APIs enable structured integration. European data sovereignty creates technical requirements that favor purpose-built solutions.

The clinical need is undeniable. Physician burnout and staffing shortages have reached crisis levels, while documentation burden continues to pull clinicians away from patient care.

We're not just building a product. We're architecting the infrastructure layer that will define how European healthcare operates for the next decade.

Every conversation will become structured intelligence, and every doctor will get their time back to do what they trained for: practice medicine.