Value leaks
Pilots work in one team and stall there. MIT found that 95% of organizations get no measurable return from generative AI. Without a shared map, no one knows which steps to move next, or what it saved.
The system of record for human + AI work in pharma
When humans + AI have clear roles,
healthcare advances.
OpenPetri maps every process, shows which steps people do and which AI does, and optimizes the split: AI takes the routine, people keep the work only they can do. You see how AI works across the whole organization. And if an AI model stops being available, Petri switches to an alternative, so no process is disrupted.
- Human
- Human + AI
- AI
The problem
Pharma is adding AI everywhere. Nobody can say who does what.
AI arrived one team and one tool at a time: a translation engine here, a literature screener there, a copilot at the agency. Nobody designed the split between people and AI, so nobody owns it.
Risk builds up
When QA or an inspector asks whether a person or a model checked something, the answer sits in someone's inbox.
People disengage
Teams hear "AI" and think "replacement". Without clear roles, adoption turns into resistance.
Source: MIT NANDA, "The GenAI Divide: State of AI in Business 2025."
Why now
AI is in the workflow. Regulators want proof of who is in charge.
AI floods the review queue
Generative AI makes it cheap to create more content, more local variants and more documents. Every piece still needs medical, legal and regulatory review, so the bottleneck moves to the human steps.
Human oversight becomes a requirement
The EU's draft GMP Annex 22 on AI requires human oversight for high-impact uses. The EU AI Act's high-risk obligations apply from December 2027. The FDA published draft guidance on AI used for drug regulatory decisions in 2025. Proof of oversight is becoming a cost of doing business.
Same teams, more work
Patent expiries and pricing pressure push every function to do more with the people it has. Deciding what AI should take is now a leadership question.
Sources: EMA / European Commission draft GMP Annex 22 (July 2025); EU Digital Omnibus on AI (in force July 2026); FDA draft guidance on AI to support regulatory decision-making for drug and biological products (January 2025).
At a glance
What OpenPetri does
-
1
Map the foundations
Every stepEvery ownerEvery sign-offPetri drafts a map of how each process really runs from your SOPs and documents. Your team checks it and adds the workarounds the SOP never mentions. Steps that need a qualified person stay locked.
Try the prototype -
2
Petri optimizes, constantly
HumanHuman + AIAIPetri scores every step on repetition, judgment, patient risk and regulatory exposure, assigns it to Human, Human + AI or AI, tracks the time it gives back and what the AI costs, and keeps re-optimizing as tools, prices, teams and rules change.
What happens when an AI goes down Always on
The product
See it on a real process
Pick a process and map it. Then optimize it with Petri for time and cost, simulate what happens under pressure, see every AI tool, system and person it depends on, and see how each person gets just their own tasks in Teams, Slack or email.
Same team, better work. Nothing here removes people. Every step keeps a named owner, and every hour AI takes on goes back to the team for strategic work.
Sample data. Owners, systems and figures are fictional.
Book a demo
20 minutes. We walk through a process you choose.
For the people doing the work
No maps to read.
Just your tasks.
Process maps are for the leaders who design the work. Everyone else simply gets their part. Petri sends each person only the steps that need them, in Microsoft Teams, Slack or email, with everything they need attached.
- Tasks come to youNo new tool to learn. Petri messages each person in the app they already use, and only when a step needs them.
- AI does the prepDrafts, checks and references arrive ready, so people spend their time on judgment, not on copying and pasting.
- Done in one clickApprove, edit or sign off from the message. The decision is recorded with the person's name, ready for QA.
Petri Morning, Laura. Two things need you today. Everything else in the campaign is handled or waiting on others.
AI draft readyDue today
Personalised email variants
12 variants built from approved modules. Check tone and fit, then approve.
Your turnDue tomorrow
Channel and sequence planning
Segments are ready. Petri suggests a three-touch sequence for you to adjust.
Resilience
When one AI goes down,
the process doesn't.
OpenPetri lets you build flexible processes. Every AI-assisted step has a ready alternative: another model, another provider, or a person. If a tool fails, becomes too expensive or is no longer available, Petri switches the step and the work keeps moving.
- PredictPetri shows which steps depend on a single provider or region, before it becomes a problem.
- PrepareEach AI-assisted step gets a pre-approved alternative, validated in advance.
- SwitchIf a tool is lost, the step moves to its alternative. Qualified-person sign-offs stay in place, and every switch is logged.
ScenarioA US AI service is no longer available in Europe
- Personalised email draftsUS-hosted language modelEU-hosted language modelRunning
- Local adaptation of claimsUS translation serviceEU translation engineRunning
- Literature screeningUS search modelIn-house modelRunning
- Medical reviewQualified personRunning
3 of 4 steps depend on US-hosted AI. Petri has an alternative ready for each.
Illustrative scenario. Tool names are generic.
Why it pays off
AI's value is won or lost in how work is organized.
The gains from AI go to companies that redesign their processes and make roles clear. That is exactly what OpenPetri does, and in pharma every day saved has a price.
of employees' time goes to activities that generative AI and other technologies could automate today.
With OpenPetriYou see exactly which of those activities sit in which step, and move them to AI one step at a time. The time goes back to your people for strategic work.
AI high performers, the 6% of companies getting significant EBIT from AI, are about three times as likely to have fundamentally redesigned their workflows (roughly three-quarters versus one-quarter).
With OpenPetriWorkflow redesign becomes a repeatable routine: map the process, mark every step, apply Petri's plan, repeat across functions.
in lost sales for each day an average drug is delayed. A day of a phase II or III trial costs about $40,000.
With OpenPetriPetri finds where work waits, between people, tools and sign-offs, and measures the days it takes out.
What a pilot proves. We measure one process before and after: cycle time, review rounds, routine hours per asset, and the share of AI-assisted steps with documented human oversight. Those four numbers make the business case for the next function.
Sources: McKinsey & Company, "The economic potential of generative AI: The next productivity frontier" (2023); McKinsey, "The state of AI" global survey; Smith, DiMasi & Getz, Tufts CSDD, "New Estimates on the Cost of a Delay Day in Drug Development," Therapeutic Innovation & Regulatory Science (2024).
Market
Start with one process.
Expand to the whole company.
- Land
Commercial content, MLR & omnichannel
High volume, highly repetitive and fully regulated. Every global pharma company runs it, AI is already arriving there, and our team has run it for years. The fastest place to show the time AI gives back to teams.
- Expand
Every function in pharma
R&D, clinical, regulatory, safety, medical, market access, manufacturing and sales. The same map, markers and guardrails, one process at a time.
- Extend
All of life sciences
Scaling biotechs, CROs, CDMOs, medtech and diagnostics. Later, any industry where AI needs human oversight.
$3.2B
Veeva's revenue in fiscal 2026, built as a system of record for life sciences. Pharma pays for systems of record. Human + AI work doesn't have one yet.
$60–110B
Yearly value McKinsey estimates generative AI could bring to pharma and medical products. Capturing it depends on deciding, step by step, what AI should do.
Sources: Veeva Systems, fourth quarter and fiscal year 2026 results (March 2026); McKinsey & Company, "Generative AI in the pharmaceutical industry: Moving from hype to reality," 2024.
Competition
Others see part of the picture.
We map the whole of it.
Today teams piece this together from tools built for something else. Ratings reflect what each category typically offers.
| How teams solve it today | Maps real work | Decides human vs AI | Audit-ready evidence | Stays current | Works across every AI provider |
|---|---|---|---|---|---|
| Pharma suites with built-in AI e.g. Veeva | Partly | Partly | Yes | Yes | No |
| Process mining e.g. Celonis | Yes | No | Partly | Yes | No |
| AI governance platforms e.g. Credo AI | No | Partly | Yes | Partly | Partly |
| Consulting projects | Yes | Yes | Partly | No | No |
| SOPs and spreadsheets | Partly | No | No | No | No |
| OpenPetri | Yes | Yes | Yes | Yes | Yes |
Neutral by design
We don't sell models or content tools. Petri routes each step to the best option, including the tools clients already own, and switches when one fails.
Designed for GxP from day one
Guardrails, audit trail and validation evidence are the core of the product, not add-ons. That's what gets past QA in pharma.
Hard to replace once adopted
The map becomes where AI decisions are recorded and signed off, and every map teaches Petri about the next one. Once QA relies on it, it stays.
Business model
Land with one process. Grow function by function.
Function heads and transformation leaders at global pharma, and operations leaders at scaling biotechs building AI-native from day one.
QA and compliance, who need evidence of human oversight for every AI-assisted step.
Annual subscription per function. It grows with the processes mapped and the AI steps Petri runs.
A 12-week paid pilot on one process, with the baseline measured in week one. Then expansion across functions, markets and affiliates.
The plan
What the seed round buys
- Interactive prototype across three pharma processes
- Wedge chosen: commercial content and MLR review
- A team with 10+ years inside six global pharma companies
- Three paid pilots with global pharma in content and MLR
- First process live in production, with a full audit trail
- GxP validation pack and ISO 27001 certification
- Expansion into a second function at a pilot customer
- Core engineering team in place
The team
We lived this problem inside global pharma
Our founder led omnichannel and digital transformation at a global pharma company, reporting to the CMO and CCO, and has worked on AI-assisted MLR review. He co-developed an EU-certified cardiac diagnostic with leading research partners, started in product at tech startups, and holds a PhD in open innovation.
10+years in pharma
6global pharma companies
Founders
ConfidentialCo-founder, AI & Data
Advisors
- ConfidentialP&C Advisor
- ConfidentialCommercial Strategy Advisor
- ConfidentialIT Advisor
Experience at
- Novartis
- Takeda
- Almirall
- Boehringer Ingelheim
- Sanofi
- Roche
Company names describe team members' professional experience. They don't imply any partnership or endorsement.
The vision
Humans at the center.
Today, OpenPetri is the map of who does what in pharma. Tomorrow, it's the operating layer for every organization where people and AI work side by side: clear processes, clear human + AI ownership, scaled across the entire company. Over time, it becomes the benchmark for how life sciences splits work between people and AI.
Every process mapped the way it really runs, not the way the SOP says.
Every step marked Human, Human + AI or AI, with a named person accountable.
AI takes the routine. People get time back for the science, the care and the ideas only they can bring.
Q&A
Questions we hear
Who is OpenPetri for?
Pharma, biotech and medtech teams bringing AI into their daily work. Function heads, operations and transformation leads, and anyone who has to answer one question: who does this step, a person or AI?
Most teams start with one process in one function, then expand.
Does OpenPetri reduce headcount?
No, and that isn't the goal. Every step keeps a named owner, even when AI does the work.
The hours AI takes on go back to the same team for strategic work: better science, closer customer relationships, sharper decisions. OpenPetri measures that time so leaders can see where it went.
Why not just use a general AI tool like ChatGPT?
A general AI tool knows a bit about everything. It doesn't know how pharma work actually runs.
OpenPetri starts with that knowledge built in: how processes like MLR review, safety case handling, launches and field engagement really move, where the handoffs break, where a qualified person must sign, and what inspectors ask. It comes from years inside global pharma.
And it isn't either/or. Keep using the AI tools you have. OpenPetri shows which steps they should take on, and which stay with people.
Isn't this a consulting project?
No. A consulting project delivers a snapshot that is out of date within months. OpenPetri is software: the map stays current as tools, teams and rules change, and every decision is recorded. It runs at software margins, not consulting rates.
What stops Veeva or an AI lab from building this?
Suite vendors build AI into their own apps. AI labs want work to run on their own models. Pharma companies run dozens of tools and several AI providers, and they don't want one vendor deciding what goes where.
OpenPetri is neutral. It maps work across every tool, including Veeva, and can switch providers when one fails or gets too expensive. A suite vendor or a lab can't credibly offer that.
How big can this get?
Pharma already pays for systems of record: Veeva reached $3.2B in revenue in fiscal 2026 selling them to life sciences. Human + AI work has no system of record yet.
We land in commercial content and MLR, expand to every function in pharma, then to the rest of life sciences and other industries where AI needs human oversight.
What's the benefit?
- Faster processes. AI takes the routine steps, so work moves faster, and you can measure by how much.
- AI where it pays. You invest in the steps with real returns, not scattered pilots.
- Clear accountability. Every step has an owner, ready for QA or an inspector.
- Teams on board. People see what AI takes and what stays theirs.
Let's talk
We're raising our seed round and looking for design partners in pharma. Tell us who you are and we'll set up a demo on a real process.