Make better AI implementation decisions. Then make the next one smarter.
Cellvara helps biotech R&D teams decide where and how AI should actually be implemented. It builds an understanding of your workflows, teams, data, systems and constraints, compares feasible AI approaches, turns the best option into an implementation-ready pilot, and learns from what actually happens during execution.
See pricing and pilot scopeBuilt for biotech SMEs & startups · Start with one R&D workflow · Evidence-backed decisions · Learns from every project
Scientific fit
High
Strong methodological match
Data readiness
Medium
Operator metadata incomplete
Implementation fit
High
Fits existing R&D workflow
Economic attractiveness
High
Clear iteration savings
Recommended Approach
Structured DoE → Active Learning pilot. Decision: proceed with a staged pilot.
Pilot Roadmap
Backed by
Cellvara is part of Google for Startups, MongoDB for Startups, Claude for Startups, ElevenLabs Startup Grants and AWS for Startups.
See how Cellvara will look
Before the full product launches, try a clickable prototype. Follow a sample IL-6 ELISA with high background: Cellvara structures the lab data, traces the likely cause, ranks the fixes and drafts the next experiment. You check and approve every step.
About 5 minutes · fictional sample data
Try the prototypeWant it on your own lab data? Join the pilot program
Have an AI workflow you're unsure how to approach?
If your biotech R&D team is considering an AI initiative but is uncertain about feasibility, data readiness, the right technical approach or how to implement it, we would like to hear about it. Start with one workflow — we will help you determine whether AI is actually appropriate, which approaches are feasible, what could block implementation, and what a measurable pilot should look like.
Currently working with innovation-focused biotech R&D SMEs and startups.