Point your phone. Get lab-grade particle size distribution in seconds. No lab. No waiting. No expensive equipment. grai replaces sieve analysis on-site.
Replace your next sieve analysis with a simple smartphone workflow.
Fill the photobox with your soil sample, position your phone, and take a photo. That's it — no special equipment beyond your smartphone (better if using a photobox).
Upload the image to grai. Our AI processes it in seconds, running a deep-learning regression to estimate the full particle size distribution.
Receive a full particle size distribution curve with d10, d30, d60, Cu, and Cc values. Export as CSV, AGS, or PDF report — ready for your engineering documentation.
Upload a soil sample image to analyze particle size distribution instantly.
Register for free to try grai4. For unlimited access, request an API key.
Auto uses EXIF data and a calibration database, assuming a 210 mm distance to the soil surface. Enter a value manually if you know your phone setup's pixels-per-mm.
Drag & drop or browse
or download a sample image to test
Analyzing particle size distribution...
grai needs your phone setup's pixel density (PPM) for accurate scale detection. Auto-detection assumes a 210 mm distance to the soil surface and a default 70° angle-of-view. If your setup differs or your device isn't in our database, use our calibration tool below.
Upload an image, then click two points on a known dimension
or drag & drop an image hereWatch the complete workflow — from data preparation to model output — and see how easy it is to predict particle size distribution with grai.
deepsoil's flagship product, grai, brings laboratory-grade precision to the field. No more waiting days for lab results.
Take a picture of the soil sample and get results in seconds using our proprietary computer vision algorithms.
Designed for the field. No specialized hardware required—just your mobile device and the grai platform.
Our AI model has been trained on thousands of samples to ensure accurate particle size distribution (PSD) mapping.
grai utilizes state-of-the-art deep learning architectures to predict the particle size distribution directly from the image, accounting for lighting, scale, and texture variations.
Start free, upgrade when you need more. No hidden fees.
Recommended dark chambers for accurate image capture
Buy Boxes + LED Strip
~€30
Drill 5 cm hole, attach LED strip, fill bottom box with soil.
Our AI-powered solution offers significant advantages over traditional methods and competitors.
Rapid, cost-effective particle size analysis that replaces traditional sieve analysis and lab equipment.
Rapid assessment of soil stability and composition for construction projects. Required for infrastructure projects every 200 m of soil investigation.
Universities and research institutions can leverage AI-powered tools for teaching and advanced research.
deepsoil is developing a comprehensive suite of AI-powered geotechnical solutions. grai is our first product, with more innovations coming soon.
Leading companies have expressed interest in piloting and testing deepsoil technology.
Successfully tested grai in the field. Currently working on mass deployment.
Leading provider of geotechnical analysis and design software. Interested in integrating grai AI capabilities.
Major geotechnical engineering consultancy exploring AI-powered soil analysis for their projects.
Specialized geotechnical company interested in field-ready analysis solutions.
Upper Austrian soil and building materials testing laboratory evaluating grai for quality assurance.
Global leader in geotechnical services, testing grai for rapid field soil assessment and quick site characterization.
Join these industry leaders and transform your soil analysis workflow.
Research institutions partnering with deepsoil to advance geotechnical AI — contributing data and receiving free grai access in return.
Using grai to cross-check and boost their sieve and sedimentation analyses.
Preparing a field campaign in Yucatán, Mexico, using grai with a foldable, travel-friendly photobox and the manual override to accommodate the shorter camera-to-sample distance.
Trialing grai on detonation experiments in sand — comparing sieve curves before and after to assess how the blast alters the soil, using a smartphone workflow.
Researching the effect of Biol, an organic fermented fertilizer, on coffee plants and soil health — applying grai's smartphone-based soil particle size prediction to support soil analysis in an agricultural context.
Expanding the dataset with soils containing a large fraction of fines to improve accuracy for silty and clayey soils, then fine-tuning grai on these data.
Collecting data samples for the machine-learning classification of soils through computer vision — directly feeding GRID's WP5 research.
Interested in an academic collaboration? Contact us.
Partnerships that power deepsoil's innovation.
The spin-off is based on innovative AI technology originally developed at the University of Natural Resources and Life Sciences, Vienna (BOKU).
The people behind deepsoil's innovative soil analysis technology.
Ph.D. in Environmental Engineering, BOKU Vienna
MBA in Project Management, WU Vienna
Passionate about bringing AI-powered solutions to geotechnical engineering and soil analysis. Enrico leads deepsoil's mission to revolutionize how we understand the ground beneath our feet.
Specialized in Machine Learning applications in Geotechnics during his Habilitation at BOKU. Experience leading tunnel construction projects.
Join the professionals using deepsoil technology to change how we see the earth.
Special pricing available for universities and research institutions.
This short tutorial walks you through every step of using grai: calibrate your phone setup, prepare the photobox, place and photograph the soil sample, then upload the image to our platform for instant AI-powered particle size distribution predictions. From field to result — in seconds, not days.