Founder & CEO (PreSeed HealthTech) - Clinical Coding Revenue Intelligence

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About the Venture Every hospital in Europe loses millions to a manual, error-prone coding process that hasn't changed in decades.

When a patient is discharged, a trained specialist reads 20–50 pages of clinical documentation and manually translates every diagnosis and procedure into standardised codes.

These codes determine how much the hospital gets paid.

In Germany, 17.5 million inpatient cases per year require manual coding. 51.5% of audited cases contain errors. €2.5–3 billion is clawed back annually by insurers through MD audits. 75% of German hospitals ended 2024 in deficit.

The coder workforce — several thousand Kodierfachkräfte, each requiring 6–12 months of training at ~€42K salary — cannot scale fast enough.

We are building an autonomous AI coding agent that reads everything the coder reads, reasons from the official coding guidelines (Deutsche Kodierrichtlinien), and enters codes into existing hospital software — in seconds, not 35 minutes.

Unlike traditional ML approaches that learn from historical patterns (and inherit their errors), our architecture reasons from the rules at inference time: when In EK publishes annual updates, we swap the guideline document.

No retraining.

No training data needed.

Every code comes with an evidence chain and DKR citation — audit-ready by construction.

The deployment model is equally differentiated: computer-use agents navigate any hospital information system (KIS) via VPN, exactly as a human coder would.

No API integration.

No IT burden on the hospital.

Deployment in days, not months.

Deep EHR integration follows as relationships deepen, creating switching costs.

The AI clinical coding market is ~$3B today, projected to reach $10–11B by 2035.

In Germany, the addressable market is €150–400M for AI coding software alone, with an additional ~€1.6B/year in audit clawbacks that better coding recovers.

US players (Coda Metrix, Fathom, Nym) have raised $600M+ but are built for American codes and EHRs.

Parallel has proven the model in France ($23.5M raised, computer-use approach validated) but hasn't entered Germany.

The German G-DRG system is wide open.

Find out more about the venture concept here.

Our Offer We don't just fund ideas — we co-build them. Join as Founder & CEO and get access to a full-stack venture studio offering designed to give you the best possible start:

• The programme runs in two phases

• Months 0–6 (Build)
• €110k ring-fenced build budget to cover founder stipends and additional specialist resource at the founders' discretion
• Founder stipends are €5,750 per founder per month, drawn from this budget
• Embedded studio team throughout: a full time venture builder, with support from a broader team consisting of a studio lead and growth marketer.

Founders build; the Studio supports.

• On-demand access to specialist support across data science, applied AI, fundraising, legal, finance, PR and commercial partnerships
• Dedicated network access from day one
• Months 6–12 (Accelerator / Spinout)
• At incorporation, the founding team will receive 70% equity in a new company set up for the venture, and the Studio 15%, both subscribed at nominal value.

The remaining 15% is reserved as an employee option pool.

• €275k cash investment goes directly into the new venture's bank account at IC approval - full founder discretion over how funds are deployed
• €175k at a €2.25m pre-money cap (SAFE/CLN)
• €100k at a €20m pre-money cap with MFN (SAFE/CLN)
• Accelerator support: a dedicated squad covering growth, product and fundraising, plus continued access to shared services

Jobs to be Done As Founder & CEO, you will be responsible for turning a strong thesis into a scaled, defensible business.

• Define the wedge.

Decide which clinical specialty, which KIS vendor, and which hospital segment you attack first — and whether v1 focuses on coding alone or includes insurer challenge defence.

• Build the coding engine.

Architect an LLM + rules engine that reasons from DKR guidelines, handles ICD-10-GM and OPS codes, and produces audit-defensible output with evidence chains.

• Ship via computer-use.

Deploy the first agent that navigates a hospital KIS like a human coder — VPN, user account, days to deploy — and prove accuracy against the human baseline.

• Win RBK as a reference site. Run a retrospective analysis on historical cases to quantify revenue left on the table, then convert to a live pilot.
• Navigate regulation. Build for BSI C5 Type 2 certification, GDPR compliance, and EU AI Act readiness — these are table stakes, not afterthoughts.
• Build the agent factory. Once coding earns trust, extend to billing, admissions, CDI — each new agent on the same infrastructure, compounding switching costs.

Your Ideal Experience We are not looking for a traditional healthcare executive or a pure AI researcher. The ideal candidate sits at the intersection.

• Experienced founder or builder capable of operating from zero to one in enterprise health-tech or AI infrastructure.
• Unique market insight or a "top 1%" advantage in clinical coding, hospital revenue cycle, health-tech AI, or German healthcare IT.
• Strong technical instincts: you can reason about LLM architectures, computer-use agents, clinical NLP, and hospital system integration — even if you are not writing the code yourself.
• Proven ability to sell into conservative, risk-averse hospital buyers and navigate German healthcare procurement.
• High IQ and EQ — comfortable speaking with hospital CFOs, clinical coders, and IT directors in the same week.
• Deep understanding of the German healthcare market. German language skills (fluency) are essential to navigate the G-DRG system, DKR guidelines, and MD audit processes.

Most importantly, you are motivated by building the system that automates the most cognitively demanding administrative process in healthcare — and turns every hospital into a customer for an expanding suite of AI agents.

This is your company. We're here to help.

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