Reproducibility is a record, not a hope.
We are building the lab notebook that makes reproducibility the default outcome of doing science, not a separate task scientists have to remember.
Why we started Provenza
Provenza started with a result that would not come back.
Our founders met at an early-stage biotech, one running assays at the bench, one building the data platform behind them. A cell-viability result looked strong enough to plan a program around. Then it stopped reproducing. For three months two scientists tried to rebuild the exact conditions that produced it. The original protocol was scattered: a reagent swap mentioned in a Slack thread, an incubation time written in a paper notebook, a lot number nobody had recorded at all. The finding was probably real. The record of how to get there was gone.
They kept asking the same question: why does software get version control and biology gets a spiral notebook? Provenza is the answer they wished they had. Capture the protocol as you work, version every change, and rebuild any run exactly.
What we hold to
Reproducible by default
If an experiment cannot be rerun, it is not finished. We capture the protocol, reagents, and conditions at the moment of work so every result carries the instructions to reproduce it.
The data belongs to the scientist
Your protocols and results are yours. We make them portable, exportable, and yours to take to any ELN or regulatory format, with no lock-in.
Precision over approximation
A lot number, a temperature, a two-minute deviation: these are the difference between a result and a rumor. We record the specifics most tools round off.
Fits the bench, not the reverse
Scientists should log by voice mid-pipette or in plain language between steps, not stop to fill in forms. We shape our software around how the work actually happens.
A bench scientist and an infrastructure engineer
Provenza is built by people who lived the problem from both sides: running the assays, and building the systems that should have recorded them.
Dr. Maya Ellison
Co-founder and CEO
Maya spent nine years at the bench before starting Provenza. She earned her PhD in molecular and cell biology from UC San Diego, then led a cell-based assay group at a Series B oncology startup, where she watched promising results stall for months because no one could reconstruct the exact conditions that produced them.
Daniel Okafor
Co-founder and CTO
Daniel builds the infrastructure that makes lab work versionable. He spent six years as a senior engineer at a data-platform company, building the systems that tracked lineage and versioning for petabyte-scale pipelines, and came away convinced that biology deserved the same rigor as production data.
Founders and advisors are fictional and illustrative.
Backed by pharma and academia
We are advised by people who have run reproducibility programs at scale, in industry and in the lab.
Dr. Priya Raman
Former VP of Translational Science at a top-ten pharma, where she ran preclinical reproducibility programs across three therapeutic areas.
Prof. Thomas Vance
Professor of Chemical Biology and principal investigator running a 20-person academic lab focused on assay development.
Elena Marchetti
18 years in lab operations and metrology, formerly head of quality systems at a contract research organization.
Reproducibility is not a compliance checkbox added at the end. It is a property of how the work is recorded, and we build the tools that make it the default.
Reproducible by default, from run one.
Start capturing protocols the way you actually work, and make every experiment rerunnable without adding a minute of paperwork.
Free for solo researchers. No card.