Loci is a free, open-source desktop workspace for scientific images. View microscopy and 3D data, count cells, annotate, measure and export traceable results without a cloud account or subscription. Use built-in analysis or bring compatible model packages. Built by a researcher and shaped by real lab workflows. Currently public beta for Apple Silicon Macs; research use only.

What real task does your product handle with GPT-6 Astra?

Loci helps researchers turn biomedical images into reviewable, reproducible results - from cell counting and fluorescence quantification to whole-slide inspection, measurements and 3D imaging. GPT-6 Astra has been the engineering agent that helped me turn those real lab needs into working software. I describe the scientific workflow and constraints, and Astra helps trace the codebase, design and implement the workflow across Electron/React/Python, debug failures, add tests and verify the packaged application while preserving provenance and local-first data handling. The resulting Loci app performs the analysis locally. This has let me, a biomedical researcher with no experience in software development, iteratively build and improve a tool around problems I encounter in real research.

Hi everyone! I’m Sid, a biomedical researcher based in Singapore.

Loci started out as a small project to help a startup here with its cell-counting workflow. The budget was limited, and buying additional imaging equipment or an expensive analysis package wasn’t a realistic option. The aim was much simpler: make better use of the images and equipment they already had, with a repeatable workflow they could inspect and reuse.

That small project made me think about a broader problem. A lab may need only a few specific analysis tools, but still face a large purchase, a complicated setup, or a workflow spread across several applications.
My goal with Loci is to make useful scientific image-analysis tools accessible regardless of a lab’s budget.

It brings multichannel image viewing, cell counting, annotations, measurements, 3D exploration, and much more into one local desktop workspace. Needs no account or subscription. The source is open to inspect, modify and extend, and researchers can use built-in methods or bring compatible models through supported Cellpose checkpoints and ONNX packages.

I use Loci in my own research, and I’m testing and currently refining it with researchers in Singapore across skin research, 3D imaging, cell-culture workflows and biomaterial studies. Real use keeps revealing what needs to be clearer, what is missing and what needs fixing. This helps me iterate and improve over time meaningfully.

Also, I’m a researcher and NOT a professional software dev. I bring the research questions and practical requirements, then test the changes against the work I actually need to do with an (obsessive) attention to detail. Codex does the rest 😅 (it does seem like you really can just build anything with OpenAI :D).

This is the first public beta currently available for Apple Silicon Macs. It's research software, with known installation and startup limitations documented on GitHub, and there is still PLENTY to improve.

I’d especially value feedback from researchers and image analysts. What image analysis task is harder, more expensive or more repetitive than it should be in your lab?

Thank you for taking a look! I hope Loci can become a useful contribution to the scientific tools our community shares :)

What real task does your product handle with GPT-6 Astra?

Loci

Open-source biomedical image analysis for every lab

Open-source biomedical image analysis for every lab