Decide which AI initiatives in R&D are worth running, and what they take in a regulated environment.
Sound familiar?
AI expected this year?
Get a basis for choosing what to run.
Not sure where to start?
Start with the step that pays off now.
IT says no, leaders say go?
Map what each initiative touches.
Pilots that never go live?
Bring QA in from day one.
More ideas than time?
Rank them by the hours they free up.
Three directions. One decision.
Each direction is laid out in timeline, cost and risk, so the trade-offs are visible and the choice is yours, on a basis you can defend.
MVP, Golden opportunity and Full ambition: from the smallest step that pays off now to the full ambition. Each with timeline, cost, risk and an estimate of the hours it frees up.
Every choice is also a choice against something, so the list also shows what isn't worth spending money on yet.
The prioritized list, the recommendation and the argument, ready to present.
For each initiative: hours freed per year, cost, time to operation, what it takes, and where it touches your QMS, documentation and validation.
Handed over in a session with your team.
How we work
Four steps from the first question to a decision you can defend.
Ambition
What AI should solve for you, not the other way around. Who in R&D, QA, IT and management has a stake, and what each of them needs to say yes.
Specification
Where the time goes in development, what is already in use (including what isn't officially approved), which systems and data are available, and which requirements and constraints apply.
Concepting
Candidate initiatives assessed against what works in operation today, not just in a demo, and mapped to where they touch the QMS.
Decision platform
Three directions, a prioritization and a recommendation, walked through with your team.
About 9 weeks in total. The plan is confirmed with you in step 1.
An estimate, not a quote.
Four weeks assumes the data is ready at the start and the right people are available when needed.
See it in practice
Fourteen AI ideas, one development department
An AI standards advisor for the development team
Which of our own tools are worth keeping
Who is involved?
QA and IT from the start, because they are the ones who have to say yes. Depending on the initiatives, also marketing, sales, finance, patents and the project teams themselves.
Do you also build the AI?
Yes, as a separate task after the scoping: a pilot ready to launch, or a working prototype on your own data. The scoping first, so the budget goes to the right initiative.
Does the list say what not to do?
Yes. It shows what isn't worth spending money on yet, and why.
How long does it take?
From about 4 weeks when most is already known, to about 14 weeks when little is. Use the plan under How we work to see your case. The plan is confirmed with you in step 1.
What do you need from us?
Data ready at the start, access to the right people at agreed times, and one named owner. That is what makes four weeks possible.
How do we start?
Book a 30-minute call. If you prefer, write to info@skibla.com or call +45 50 30 75 73.
Our guiding principles
Built for tough decisions
AI ranked on hours saved and risk.
Hands-on, not hands-off
Digital tools built in regulated R&D.
AI-enabled, human-led
AI does the legwork. QA signs off.