Zorost Intelligence builds production-grade machine learning and deep learning systems designed for mission-critical, domain-sensitive use cases. From aviation safety forecasting to defense risk modeling and smart infrastructure planning, we deliver intelligent systems that learn, adapt, and act in real-time.

We specialize in advanced supervised, unsupervised, and reinforcement learning frameworks—with pipelines powered by Databricks, Azure ML, SageMaker, and hybrid edge-cloud inference architectures.

What We Deliver:

• Model Design & Custom Training
  Build and fine-tune models using regression, classification, anomaly detection, time-series forecasting, NLP, and image-based neural nets (CNNs, ViTs, RNNs).

• Large-Scale Data Processing
  Use Apache Spark, Delta Live Tables (DLT), AWS Glue, and Microsoft Fabric to power high-volume ETL, feature generation, and model-ready preprocessing pipelines.

• Real-Time ML Inference
  Enable low-latency predictions on telemetry, sensor, or user input streams using AWS SageMaker Endpoints, Azure ML Real-Time Scoring, and Kubernetes-deployed models.

• MLOps & Lifecycle Management
  Implement MLFlow, Azure Machine Learning Studio, or SageMaker Pipelines to manage versioning, retraining, lineage, explainability, and drift monitoring.

• Neural Networks & Deep Learning Architectures
  Train custom CNNs, transformers, LSTMs, and autoencoders using PyTorch, TensorFlow, Hugging Face, and JAX across multimodal datasets (text, imagery, time series).

• AI-Powered Recommendation & Personalization Systems
  Deploy personalized interfaces and alerts using collaborative filtering, sequence modeling, and hybrid deep recommender systems.