UnixonAI
MLOps & Data Automation
End-to-end pipelines for training, validating, deploying, and monitoring AI at scale.
Operationalizing Machine Learning
Model Lifecycle Management
Track, version, and retrain models seamlessly. Automate CI/CD for AI development and deployment pipelines.
Data Validation & Drift Detection
Ensure training/serving consistency. Detect anomalies, distribution shifts, and missing features in real-time.
Automated Retraining
Schedule model retraining based on triggers: performance decay, data thresholds, or business cycles.
Our MLOps Stack
MLflow & Weights & Biases
Track experiments, visualize metrics, and reproduce training runs easily across teams.
Docker & Kubernetes
Ship models as containers. Deploy across cloud or edge clusters with full resource orchestration.
FastAPI & gRPC Services
Serve models through lightweight, high-performance APIs—supporting REST and real-time inference.
Data Pipelines & Automation
Data Ingestion
Connect to sensors, databases, APIs, and file systems to ingest data continuously or on schedule.
Feature Engineering
Automate feature extraction, normalization, and transformation across batch and real-time workflows.
ETL & ELT Pipelines
Build scalable Extract-Transform-Load and Extract-Load-Transform processes using Airflow or custom triggers.
From Model to Value, Faster
UnixonAI’s MLOps platform ensures your AI innovations stay reliable, scalable, and maintainable in production.
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