In our benchmarks, MotionCorr CC outperformed Relion’s CPU-based motion correction running on the CryoCloud platform across all detectors, movie sizes, and frame counts.

With GPU acceleration, MotionCorr CC delivers:
⚡ Up to 4× faster throughput
⚡ Up to 5,000 movies/hour
⚡ 50–75% lower compute cost
⚡ Full compatibility with downstream polishing & CTF refinement

🧠 Six new algorithms added since launch, including CryoCloud Picker and CryoCloud MotionCorr, bringing major improvements in speed and quality
⚡ Automated workflows and rapid development across the entire platform
🔐 ISO 27001-certified processes

3 years in numbers:
💻 Over 100,000 GPU hours of data processing
🔬 Thousands of datasets processed across cryo-EM & X-ray
🚀 355 production deploys + 2,158 staging deploys – steady improvements week after week
👥 A growing global user community (hundreds of users including trials)

And if you missed the last release... with v2.15, we added three new cool structural-biology tools to the platform – LocScale2, CryoSieve, and EMReady!

Catch up here → connect.cryocloud.io/release-note...

If you’d like to continue any of the discussions from Basel or take a closer look at the platform, feel free to reach out at [email protected]!

• Reliable particle picking and QC, such as 2D class selection & map anisotropy, remain central for scaling automated workflows
• The bottleneck has shifted from compute → expertise → data management
• Structured data & faster feedback loops are essential for routine, high-throughput work

Read more about MotionCorr CC in this post: bsky.app/profile/cryo...