aitoo helps scientific and R&D teams build image-analysis workflows they can reproduce, scale, and trust.
We combine expert consulting with quai, our platform for decision-grade image analysis.
We work with pharma, biotech, diagnostics, and translational research teams that rely on microscopy, pathology, high-content screening, or other biomedical imaging workflows.
For teams developing image-based assays, segmentation workflows, or quantitative imaging readouts that need to be reproducible and easier to maintain.
For teams building reliable pipelines around imaging models, including model tracking, uncertainty, calibration, scalable inference, and traceable outputs.
For teams turning research code, notebooks, or prototypes into tested, documented, and maintainable software workflows.
We bring deep expertise in computational imaging, biomedical analysis, and scientific software engineering. We help teams move from promising methods and research prototypes to robust software workflows that can be reproduced, maintained, and trusted when results matter.
Grounded in domain knowledge, peer-reviewed methods, and practical validation.
Software designed for reproducibility, maintainability, and reliable operation.
We work with your scientists, engineers, and data teams to build workflows that fit your environment.
Whether you need to evaluate a segmentation approach, rescue a fragile analysis workflow, or prepare an imaging pipeline for larger-scale use, we help you move from prototype to reproducible scientific software.
Request a workflow reviewA focused review of your current image-analysis workflow: data flow, segmentation quality, reproducibility, scaling bottlenecks, and maintainability risks. You receive a prioritized technical roadmap.
A fixed-scope pilot that turns one dataset and one analysis question into a reproducible training, inference, and evaluation workflow.
Design and implementation of robust image-analysis and inference pipelines that can be maintained, tested, versioned, and scaled.
Targeted support for scientific software engineering, ML workflows, reproducibility, and image-analysis software quality.
quai is our platform for decision-grade image analysis, built for biomedical workflows where accuracy and traceability are non-negotiable. It helps teams run reproducible segmentation workflows, track models and results, quantify uncertainty, and monitor calibration. The result is a clearer view of when to trust the output and when expert review is needed.
Track model versions, experiment metadata, and performance across runs. Keep model outputs connected to the configuration, data, and code that produced them.
Define and run segmentation workflows as reproducible pipelines, from data preparation to full-image inference, quality checks, and traceable outputs.
quai surfaces where the model is uncertain, so human review is targeted rather than exhaustive. Know which outputs to act on and which to verify.
Use uncertainty and quality signals to prioritize samples for review, annotation, and retraining — focusing expert effort where it has the highest value.
Confidence scores that mean what they say. quai tracks calibration over time and flags when model reliability drifts from its stated uncertainty estimates.
Run batch inference on large biomedical imaging datasets, with deployment options for local, on-premise, cloud, or hybrid environments.