Every model decision, signed and independently verifiable.
AML is read from five signals scattered across separate instruments. Axiisium fuses them into one calibrated call, and binds each prediction to a record a regulator and a clinician can verify.
AML is diagnosed from many signals at once, and the decisive ones rarely reach a single model together. Some genetics that drive treatment are written in the cells; some are not. Fusing the signals reaches the ones a single view cannot.
Bone-marrow and blood-smear cell morphology.
Immunophenotype for classification and residual disease.
Karyotype and FISH signals morphology cannot see.
Mutation and fusion status: NPM1, FLT3, the wider panel.
Age, blast percentage, and labs that frame the prediction.
Rank which trial candidates to sequence first for a target mutation, so a sponsor fills an NPM1-defined cohort with fewer assays and a signed record of every selection. It ranks, it never decides; sequencing always confirms; a recall floor bounds what it can miss.
Research-use todayA signed assessment that evolves from day zero to final molecular: a provisional read while sequencing runs, an ELN-2022 risk class, and a therapy-eligibility map, each claim tied to the signal that triggered it. Decision support that defers the hard calls to molecular and the clinician.
On a De Novo device pathwayThis runs the real morphology model on your image and returns a blast call with a calibrated confidence, then binds it to a tamper-evident, independently verifiable record. The molecular confirmation runs separately on the NVIDIA Clara Parabricks pipeline; morphology never calls the hard mutations on its own.
We are looking for clinical and pharma design partners in hematology. If you run acute myeloid leukemia trials or hold aligned multimodal data, we would like to talk.