Agentic AI for drug safety, documented for validation.
Most PV teams don’t need another AI platform. They need someone who knows both the safety database and the model — and can put the two together with the evidence trail an inspection calls for. That’s what we build.
A minute on what we automate — and where we deliberately stop.
The same argument this page makes, in sixty seconds: the work that should be automated, the judgment that should not, and the evidence that has to exist either way.
Decide what to build, or build what you have decided.
Some teams arrive with a shortlist and need it built. Others need to work out what is worth building at all. Both are engagements we take.
Every one of these proposes. A person disposes.
Automation here is drafting, matching and routing — the parts of a case that are mechanical once the rules are written down. Each output arrives with its rationale and its source record, and waits for someone to accept it.
Seriousness, expectedness and causality are assessments a person signs. A model can assemble the evidence for them, show its reasoning and flag what looks unusual — and that is where it stops. We have removed an automated flag from a client’s system for exactly this reason, and we would do it again.
The AI is the easy part. The evidence is the job.
We came to AI through computer system validation, not the other way around. Every model we deploy arrives with the same documentation trail we’d hand an auditor for an Argus upgrade — because sooner or later, someone will ask for it.
Talk through your validation approachThe same controls as any other change.
AI in a safety process is still a change to a regulated workflow. It is specified, tested and evidenced the way anything else touching case data would be.
On infrastructure you control.
Safety data does not leave your environment to be processed by someone else’s service.
Curious what AI could actually take off your plate?
We will walk your workflows with you and say plainly which ones are worth automating — and which are not.
Book an AI readiness review
Agentic AI for drug safety, documented for validation.
Most PV teams don’t need another AI platform. They need someone who knows both the safety database and the model — and can put the two together with the evidence trail an inspection calls for. That’s what we build.
A minute on what we automate — and where we deliberately stop.
The same argument this page makes, in sixty seconds: the work that should be automated, the judgment that should not, and the evidence that has to exist either way.
Decide what to build, or build what you have decided.
Some teams arrive with a shortlist and need it built. Others need to work out what is worth building at all. Both are engagements we take.
Every one of these proposes. A person disposes.
Automation here is drafting, matching and routing — the parts of a case that are mechanical once the rules are written down. Each output arrives with its rationale and its source record, and waits for someone to accept it.
Seriousness, expectedness and causality are assessments a person signs. A model can assemble the evidence for them, show its reasoning and flag what looks unusual — and that is where it stops. We have removed an automated flag from a client’s system for exactly this reason, and we would do it again.
The AI is the easy part. The evidence is the job.
We came to AI through computer system validation, not the other way around. Every model we deploy arrives with the same documentation trail we’d hand an auditor for an Argus upgrade — because sooner or later, someone will ask for it.
Talk through your validation approachThe same controls as any other change.
AI in a safety process is still a change to a regulated workflow. It is specified, tested and evidenced the way anything else touching case data would be.
On infrastructure you control.
Safety data does not leave your environment to be processed by someone else’s service.
Curious what AI could actually take off your plate?
We will walk your workflows with you and say plainly which ones are worth automating — and which are not.
Book an AI readiness review