The first five minutes of an analysis shouldn't be the hardest part. But for anyone working with large sequencing or spatial files, getting data into a platform has often been exactly that: slow, opaque, and quick to fail on a malformed file. We've spent real engineering effort on the front door, and it shows.
Uploads rebuilt for real-world file sizes
Uploads now run in parallel and stream directly to storage instead of buffering in memory, a dramatic speed-up for the big FASTQ, RDS, and spatial datasets that have become the norm. The redesigned upload page shows live status as each file is verified and confirmed, so an upload is never a black box. And clearer error reporting catches malformed GZIP files and mismatched FASTQ pairs up front, instead of letting them fail an analysis later. Large downloads got the same treatment, streaming so multi-gigabyte exports don't time out or exhaust your browser.
A redesigned New Experiment page
Every analysis starts on the same page, so we rebuilt it from the ground up for clarity and speed. Experiment types, upload options, and launch settings are easier to find and configure, and there are fewer steps between choosing an analysis type and launching it.
nCounter that fits real studies
Real nCounter studies don't always fit on one reagent lot, and now they don't have to be split apart to be analyzed. Multi-lot support lets you keep an experiment whole even when samples were run across different cartridge lots, with QC and normalization adapting automatically to the design.
As datasets keep getting larger and study designs keep getting messier, the platforms that win will be the ones that make scale feel effortless. There's a forward-looking reason this matters, too: the smarter, increasingly AI-assisted analysis we've been steadily investing in is only ever as good as the data flowing into it. A faster, cleaner front door means more high-quality, well-structured data landing in one consistent place: the raw material for the data-intelligence work that years of this groundwork have been building toward. Removing friction at the start of every analysis is some of the highest-leverage work we do: it's time given directly back to science, and fuel for what comes next.
