Failed experiments rarely make it into publications. As a result, researchers across labs unknowingly repeat the same unsuccessful approaches — wasting time, resources, and momentum.
Synes captures experimental attempts in a structured format and makes them searchable across similar research contexts — turning dead ends into direction.
Synes fits the way research actually works — from academic discovery to commercial development.
Scientific research produces far more knowledge than what ultimately appears in a paper, protocol, or formal record. The reasoning behind an experiment — what was tried, what changed, why a decision was made, what failed, and what was learned along the way — is often distributed across notebooks, files, messages, meetings, and individual researchers.
That context is especially valuable because experimental work is inherently iterative. Researchers rarely move directly from hypothesis to result. They troubleshoot, modify parameters, compare prior attempts, revisit old decisions, and rely heavily on knowledge accumulated by the people around them. Yet most research software is designed to store records rather than preserve this evolving history in a form that can be easily recovered and reused.
Synes is exploring how experimental context can be captured, structured, and connected as research happens. The goal is to create a persistent memory of a team's work: one that helps researchers understand how an experiment evolved, identify relevant prior attempts, recover the reasoning behind past decisions, and carry that knowledge forward into future work.
A small team working across research, engineering, and the wet lab.
Modern research teams generate an enormous amount of knowledge through everyday experimentation. Much of that knowledge never becomes a formal result. It lives in the adjustment someone made after an experiment failed, the explanation given during a lab meeting, the parameter change written in the margin of a notebook, or the experience a researcher develops after months of working on the same problem.
Over time, this context becomes fragmented. Projects evolve, protocols change, researchers graduate or move on, and teams are left reconstructing decisions from incomplete records and individual memory. The data may still exist, but the understanding around it often does not.
Synes was started around a simple idea: a research team should not have to rediscover what it has already learned.
We are building a persistent memory layer for experimental research that helps teams preserve the context behind their work, connect related experiments and decisions, and make that knowledge available to the people who need it later.
Synes is not intended to replace the tools researchers already use to record experiments or store data. Instead, it sits across that fragmented history and helps make the knowledge within it easier to recover, understand, and reuse.
Our long-term aim is to make research more cumulative at the team level: when one researcher learns something, that understanding should remain useful to the next researcher, the next experiment, and the next project.
Interested in Synes, collaborating with us, or learning more about what we're building? We'd be glad to hear from you.
Start exploring experimental knowledge with Synes.