Notes & deep dives
Engineering notes, method explainers, and perspective from the Ozette team.
Putting Claude Science on top of Ozette
Getting your flow cytometry data into Ozette is one of the highest-leverage moves a translational immunology program can make. Once processed, each dataset becomes a queryable, annotated, context-rich object an AI agent can reason over — and at pharma scale, silos dissolve as data from different trials, panels, and instruments becomes uniformly comparable. Available today, whether or not you're already on Ozette, we can build your structured immune-data corpus and enable you to connect it to any agentic reasoning engine — through our MCP server.
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CYTO 2026 in the Bag
That's a wrap on CYTO 2026 in West Palm Beach — the partnership, talks, and posters that made it a standout week for Ozette.
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Ozette Resolve: Filtering Out Contaminants from Single-Stain Controls
Generating single-stain controls is a critical step for the correct unmixing of spectral cytometry datasets. This is because unmixing relies on the…
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Ozette Resolve: Why We Built It and Optimizing Use (Part 1)
Are you regularly generating spectral cytometry data? If so, do you:
Read →On complexity, decision making, and unintended consequences.
This is a post about complexity, complex systems, how they break down, how that impacts decision making and stakeholders, and how all of this has motivated…
Read →Welcome to the Ozette Blog: Generating Quality Cytometry Data at Scale
Cytometry — encompassing spectral and conventional cytometry and mass cytometry — is unquestionably the premiere single-cell profiling assay technology for…
Read →Talk with an Ozette scientist.
See what unbiased, reproducible cytometry analysis looks like on your own data.