AI-Driven DevOps & Cloud Services

AI Services

MLOps & AI-Driven DevOps for Scalable Infrastructures

From MLOps to fully automated infrastructure, we help organizations build, deploy, and scale AI-powered systems with speed, accuracy, and confidence. Our solutions keep your business agile, intelligent, and ready for the future.

By integrating AI into DevOps, we shift operations from reactive to proactive—enabling predictive analytics, automated monitoring, and self-healing infrastructure. This accelerates deployments, optimizes resources, and boosts security, compliance, and efficiency.

Whether managing ML pipelines or modernizing infrastructure, our AI-driven MLOps and DevOps services give you a strategic edge.

Why Cloud-Native + AI

Cloud-native development and AI together create a powerful foundation for modern enterprises. Beyond scalability and cost efficiency, AI is transforming how DevOps and Infrastructure are managed:

  • AI-Powered DevOps
    Machine learning models and intelligent automation enhance CI/CD pipelines by predicting failures, optimizing test coverage, and accelerating release cycles. AI-driven observability tools can detect anomalies before they impact production, enabling teams to resolve issues proactively.
  • Smarter Infrastructure Management
     In dynamic cloud-native environments, AI enables predictive autoscaling, intelligent load balancing, and capacity planning—ensuring resources are optimized while maintaining peak performance. AI-based monitoring systems learn from patterns in logs and metrics, allowing teams to detect bottlenecks, security risks, or inefficiencies automatically.
  • Resilience & Security
     AI models can detect unusual behaviors across infrastructure (e.g., traffic spikes, latency anomalies, or potential intrusions) much faster than manual monitoring, ensuring resilient and secure operations at scale.

Scalable Infrastructure, Automation, and Observability for AI Workloads

What We Do

At Unified Techs, we bridge the gap between modern DevOps practices and artificial intelligence adoption. Our AI-related DevOps services help startups and enterprises confidently deploy, scale, and monitor AI/ML workloads in secure and automated cloud environments.

AI Infrastructure Automation & MLOps Enablement

Unlock faster model delivery and experimentation with automated, production-grade infrastructure tailored for machine learning teams.

Our capabilities include:

  • Infrastructure as Code (IaC) using Terraform or AWS CDK for reproducible AI stacks
  • Scalable GPU/CPU provisioning with EKS, ECS, or Azure ML
  • MLOps pipelines using SageMaker, Kubeflow, Airflow, or Argo Workflows
  • CI/CD and GitOps for model training and deployment workflows
  • Isolated cloud environments for data science experimentation

Ideal for:
 AI/ML teams looking to streamline operations from data preprocessing to model deployment, without managing low-level infrastructure.

Secure & Scalable AI API Hosting

Serve AI models in production with zero-touch deployment and autoscaling APIs that meet performance and compliance standards.

We offer:

  • Dockerized AI/ML models deployed on ECS Fargate, Lambda, or Kubernetes
  • Secure API Gateway setup with throttling, WAF, and authentication
  • Blue/green or canary deployment strategies with rollback capabilities
  • Full observability using CloudWatch, Datadog, or OpenTelemetry
  • Cost-optimized hosting using spot instances or serverless options

Ideal for:
 Startups and enterprises delivering real-time AI features to customers via APIs or SaaS platforms.

AI-Ready Data Pipeline Modernization

Ensure your data architecture is optimized for training, inference, and AI feedback loops.

We deliver:

  • Event-driven ingestion using Kafka, Kinesis, or EventBridge
  • Serverless ETL with AWS Glue, Step Functions, or Azure Data Factory
  • Integration with Redshift, Snowflake, S3, or Lake Formation
  • Schema enforcement, data validation, and encryption at rest/in transit
  • ML-triggered retraining automation from pipeline events

Ideal for:
 Organizations building or modernizing platforms that rely on high-quality data for real-time or scheduled AI operations.

AI-Enhanced DevOps Monitoring & Remediation

Reduce downtime and improve MTTR with observability solutions powered by AI.

What we implement:

  • ML-based anomaly detection via Datadog, New Relic, or AWS DevOps Guru
  • Log enrichment and classification using Fluent Bit and OpenTelemetry
  • Predictive alerting and smart thresholds for complex systems
  • Automated remediation via Lambda, Step Functions, or Runbooks
  • Custom dashboards for AI pipelines and model performance metrics

Ideal for:
 SRE and operations teams needing proactive issue detection and intelligent incident response in large-scale microservices environments.

How We Work

Assessment & Roadmap

Understand your AI maturity, business value, and infrastructure needs.

Design & Build

Architect robust AI pipelines leveraging cloud-native best practices.

Deploy & Operate

Seamless CI/CD, auto-scaling, full-stack observability.

Optimize & Extend

Continuous improvements with feedback loops and performance monitoring.