PyTorchGPUAWS g5 / p4
Technology
We build with GPU inference and training. The stack is meant to run in the cloud, in production.
GPU compute
What runs in each product today
- PyTorch with GPU acceleration for predictive model training
- Inference on AWS GPU instances (g5, p4)
- Embeddings and vector search (JurixSolve RAG)
- Time-series models on regasification telemetry (GasSolve)
- Population risk scoring (HealthSolve)
- Production inference optimization (roadmap)
Machine Learning
- PyTorch
- Python
- Scikit-learn
- MLOps pipelines
NLP / Legal (JurixSolve)
- GPU semantic embeddings
- Vector search (FAISS)
- Procedural RAG
- Stage classification
Infrastructure
- AWS (EC2 GPU, Lambda, S3)
- Amplify + CloudFront
- Amazon SES
- CI/CD
GPU Compute
- PyTorch + GPU
- AWS instances (g5/p4)
- Batch and online inference
- Model monitoring
Workloads by product
- Clinical and family risk prediction, city/department breakdown, and EPS profiling (HealthSolve)
- Real-time pressure, temperature and IoT monitoring with time-series models and alerts (GasSolve)
- Procedural drafting assistance and similar Colombian case-law retrieval (JurixSolve)
- ETL pipelines for RIPS, industrial data, and judicial publications