Real programs already run on spcfy.
spcfy is not a concept waiting for its first user. It is the shared layer underneath multi-country consortia, decade-long inventories, transnational corridors, and the daily client work of a commercial lab. Here is who relies on it, and how.
Same data flow, three ways to enter.
The reference stories below are grouped by the role you play in the data flow. Jump to the one that matches your work.
How spcfy is used across different biodiversity programs.
From international forest research to an insect survey along Germany's Green Belt and research in a national park, spcfy provides a shared workspace for processing, exploring and reusing biodiversity data.
A shared workflow for collaborative research
BioComp investigates how climate and forest management affect decomposer communities and wood decomposition. spcfy supports this collaboration with a shared bioinformatics workflow and documented processing versions, helping teams bring results from separate analysis orders together.
Insect diversity across 100 sites
From April to August 2025, 500 insect samples were collected at 100 sites along Germany's Green Belt, with one sample per site each month. The survey recorded approximately 7,000 species. spcfy provides the shared environment for processing and exploring the survey's DNA metabarcoding data.
Research data that teams can build on
Arthropod research in the Bavarian Forest National Park spans different projects and research teams. spcfy supports data reuse through a shared repository with documented analysis settings. Researchers can revisit earlier results and assess which datasets are suitable for a joint analysis.
*OTUs are groups of similar DNA sequences used in analysis. Their number is not equivalent to the number of species. Comparisons across datasets depend on compatible sampling methods, DNA markers and laboratory protocols, as well as consistent analysis settings and taxonomic reference versions.
The labs behind the data.
One shared standard, across the labs that run on spcfy. This is what it looks like when a lab stops treating the pipeline as a problem to solve and starts treating it as infrastructure.
MetaGen runs environmental DNA and metabarcoding programs across Brazil's biomes, from field sampling design to validated species lists for research, conservation and environmental licensing. Molecular work follows a single, standardized oligo-tag PCR protocol; bioinformatics runs on spcfy.
"Every report we deliver ships with the raw data behind it, every filtering record included. spcfy is what makes that possible at the volume we run."
AIM.science is where spcfy was born. The platform was built around their workflows, and they have run on it ever since.
"spcfy standardizes our routine data processing and reporting, giving our team more time to interpret results and support our clients."
Don't take our word for it. Test it against yours.
The MAP preprint compares COI metabarcoding pipelines using ten arthropod bulk samples containing 11,509 specimens. High-quality, BIN-eligible barcodes were recovered from 10,903 specimens, and the study reported 1,700 Barcode Index Numbers (BINs).
Although this benchmark focused on COI metabarcoding, spcfy was designed from the beginning as a marker-independent platform, staying closely compatible with the Barcode Index Number (BIN) framework, the gold standard for animal DNA barcoding and an important foundation for the COI research community.
Read the preprint →Prosser et al. (2026), bioRxiv, version 2. Preprint, not peer-reviewed.
With thanks to Sean Prosser, Ken Thompson, Paul Hebert, and the entire team at the Centre for Biodiversity Genomics for this contribution to transparent benchmarking in biodiversity genomics.
Each pair links one sample's barcode and metabarcode result. Illustrative, not the study's plotted values.
These findings provide benchmark evidence for the COI dataset tested. To assess how spcfy supports your own research, compare its results with your current workflow using your own sequencing data.
Run the same sequencing data through both pipelines to explore how analysis choices affect your results. If something you need isn't covered yet, that's a conversation we want to have.
Benchmark your pipeline against spcfy
Compare sequence clustering, taxonomic assignments and diversity estimates side by side to assess how each workflow supports your research question.
Start a free trial and run a comparison →Missing a marker, method, or database?
Want to use spcfy but your amplicon, pipeline variant, or reference database isn't covered yet? Tell us what your science needs. We build and maintain the standard layer. You keep the expertise.
Tell us what you need →
Got interested?
Whether you compare data, produce it, or make meaning from it, there is already a version of your work running on spcfy.
Questions first? Write to us at hello@spcfy.io