Three powerful approaches to transforming your infrastructure through AI
From weeks to minutes: Let AI build your infrastructure
We use AI to automatically create and manage end-to-end infrastructure environments — reducing setup time from weeks to minutes. Our system intelligently generates configurations for compute, storage, and networking, eliminating repetitive DevOps tasks and allowing engineering teams to focus on innovation instead of maintenance.
Automatically provision servers, containers, and clusters with optimal configurations based on your workload requirements.
Intelligent monitoring and alerting systems that detect issues and automatically take corrective actions.
Secure, scalable logging and observability pipelines that provide deep insights into system behavior.
Repeatable deployment pipelines that accelerate your release cycles and reduce errors.
AI-powered performance tuning and cost optimization that runs automatically in the background.
Built-in security best practices and compliance controls applied automatically to all infrastructure.
Describe your infrastructure needs in plain language or use our templates
Our AI analyzes requirements and generates optimal Terraform, Kubernetes, and config files
Infrastructure is provisioned automatically with monitoring and logging enabled
AI monitors, optimizes, and heals your infrastructure automatically
Control your infrastructure through conversation
Our AI ChatOps product integrates directly into collaboration platforms like Slack or Teams to provide instant operational control through natural language. Teams can query, deploy, monitor, and troubleshoot systems simply by chatting with an intelligent assistant that understands infrastructure context.
Understands your infrastructure, team permissions, and operational context to provide relevant actions.
Role-based access control ensures team members can only perform authorized actions.
Works seamlessly with Slack, Microsoft Teams, and other collaboration platforms.
Get notified about critical issues before they impact your users, with suggested remediation.
Complete audit logs of all operations performed through ChatOps for compliance requirements.
AI learns from your team's patterns and suggests optimizations over time.
Purpose-built infrastructure for AI workloads
We design and optimize infrastructure for AI and ML workloads, with deep expertise in GPU orchestration, distributed data processing, and elastic scaling. Our systems are built for efficiency, scalability, and speed, enabling data science teams to iterate faster and deploy AI models at scale.
Efficient management of GPU resources across your cluster with automatic scheduling, resource pooling, and cost optimization for training and inference workloads.
Handle massive datasets with distributed processing frameworks optimized for ML workflows, featuring automatic partitioning and parallel processing.
End-to-end ML pipelines with elastic scaling, experiment tracking, and automated resource scheduling for efficient model development.
Deploy and manage ML models across multiple cloud providers with unified operations, ensuring flexibility and avoiding vendor lock-in.
Optimized GPU utilization and distributed training
Intelligent resource allocation and spot instance usage
Parallel experimentation with automated tracking
Reliable infrastructure for production ML systems
Choose the solution that fits your needs, or let us help you build a custom approach.