Go Grow AI
Tech that serves you
Data Engineering
Data infrastructure
Pipe lines
Machine learning
Production systems
Monitoring
Software development
Backend development
Microservices
Code reviews
Dev ops
CI/CD
Automated testing
K8s
Azure
Google Cloud
Amazon
Deep learning
Classifiers
Text analysis
Speech-to-text
Text-to-speech
Computer vison
Object detection
Segmentation
Super resolution
Optical Character Recognition (OCR)
Machine learning
Recommendation systems
Probability of Default (PD)
A/B testing
Churn prediction
AI for medical diagnosis
Develop AI-first diagnostics
Collect an AI-driven dataset
Build strong classifiers
Solid experimental design & validation
AI lab
AI guides experiments
Maximize information learned
Minimize experiments
Automate experiments
AI for optics
Get signal out of your sensors
Custom deep learning models
Lidar processing
UV spectroscopy
Raman spectroscopy
SERS spectroscopy
Deep learning research
On-premise development environment
4090 Deep learning rig
Advantages
Train large language models efficiently with RTX4090 tensor cores
Avoid large cloud bills
Keep your data on premise
4x cheaper than comparable servers from large vendors
6x RTX4090 PCIE 4.0x16, 32 core CPU, 512GB memory, 4 TB nvme SSD, 2x 10G Ethernet, IPMI Priced around € 20 000
3090 Deep learning rig
Advantages
Highest possible cost efficiency thanks to used RTX3090 GPU's
4x cheaper than comparable servers from large vendors
Empower your your data science team with the best value for money
9x RTX4090 PCIE 4.0x16, 32 core CPU, 512GB memory, 4 TB nvme SSD, 2x 10G Ethernet, IPMI, Priced around € 17 000