Hi everyone - we’re a small militant team building iLABS; a web-based platform with the ultimate goal of expanding access to deep learning tools for reproducible in vitro data analysis.
We designed our interface to explicitly help researchers analyze 2D/3D cell culture image stacks without writing custom scripts or managing GPU infrastructure. The focus is on quantitative, reproducible readouts from time-series imaging experiments.
Current capabilities include:
- AI models optimized for live-cell data (with options for fine-tuned models)
- Cell segmentation and tracking across time-lapse datasets
- Quantitative readouts for cell motility, growth, morphology, and viability/toxicity
- Support for batch processing of large image stacks
- Web-based workflow (no local installation required)
Our goal is not to replace existing open-source tools, but to complement them by expanding access for biologists who can’t code but want fast, scalable and accurate analysis.
We’re currently:
- Running a closed beta
- Actively incorporating user feedback into model performance, metrics and UX
- Looking for users working with live-cell imaging (migration, proliferation, phenotyping, drug response, etc.)
If this sounds relevant to your work, know someone who might find this useful or you fancy playing with novel in vitro tools, we’d be glad to hear from you.
Thanks!
Sesan