HPC & cluster design
Sizing, architecture and deployment of compute clusters: Slurm scheduling, high-speed interconnects, storage and monitoring.
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Churn, demand, risk, pricing, predictive maintenance — supervised models tuned to your KPIs.
Personalization systems that improve conversion and engagement.
Text classification, entity extraction, document intelligence and image-based automation.
Feature stores and pipelines that make model inputs reproducible and reliable.
CI/CD for models, automated retraining, drift detection and monitoring in production.
Evaluation, explainability, bias assessment and documentation for regulated environments.
Churn prediction with action-oriented intervention workflows
Predictive maintenance for industrial equipment
Document intelligence to automate back-office processing
We design, size and deploy the compute infrastructure your models need — from a single GPU workstation to HPC clusters, down to the edge.
Sizing, architecture and deployment of compute clusters: Slurm scheduling, high-speed interconnects, storage and monitoring.
GPU infrastructure across the CUDA/TensorRT and ROCm ecosystems: selection, drivers, virtualization, orchestration and cost optimization.
On-device intelligence with Google Coral and NVIDIA Jetson: model quantization (TensorRT, ONNX, TFLite), power budgets and fleet deployment.
Training delivery is a transversal activity across all our practice areas — every engagement can include knowledge transfer.
Practical training on model development, feature engineering, deployment and MLOps practices for ML engineers and data teams.
Formats: workshops, custom programs, executive briefings and coaching — delivered on-site or remote, in English or Spanish.
No. We build the system, operate it with you, and train your team so you can own it — or we keep operating it under a support agreement.
Tell us about your challenge. We'll come back within one business day with a first assessment.
Discuss this area with us