AI-Savvy MLOps Teams, On-Demand
Work with top-class MLOps teams with AI expertise to set up, manage, and scale your AI infrastructure, without the cost or complexity of hiring in-house. Our teams help deploy the latest LLMs on your cloud infrastructure, and set you up with monitoring and CI/CD scripts, so you can build AI faster.
Trusted by Startups and Unicorns
How We Ship AI Fast with Enterprise-Grade MLOps
Leverage our expertise in AI-ready infrastructure and dedicated MLOps microteams to design, deploy, and scale production-grade ML systems — faster, securely, and cost-effectively
Fractional MLOps Expertise
Ship AI Faster Without the Costly Overhead
Skip costly hires. Get vetted MLOps specialists when you need them, delivering faster deployments and higher ROI.
We manage the entire ML lifecycle: from cloud infrastructure setup and CI/CD pipelines to container orchestration, monitoring, and database optimization so you can focus on growth.
Secure & Scalable AI Deployments
Sovereign AI, Built for Modern Systems
Deploy LLMs, RAG pipelines, and autonomous AI systems fully within your cloud, on-premises, or hybrid environments — keeping your data, models, and IP secure.
Our MLOps expertise ensures production-grade deployments with high performance, reliability, and observability from day one.
How We Help You Grow
✔ Deploy LLMs, RAG pipelines, and AI apps in weeks, not months
✔ Avoid expensive hiring — pay only for the expertise you need
✔ Scale AI capabilities without re-architecting your systems
✔ Ensure uptime, performance, and compliance from day one
What Our Teams Deliver
End-to-end MLOps solutions to design, deploy, and scale secure, production-grade AI infrastructure.
Cloud Infrastructure for AI & Data
Architect and manage scalable AI infrastructure on AWS, GCP, or Azure.
Seamless CI/CD for AI Systems
Ship models and updates faster and more reliably.
Containerization & Orchestration
We containerize applications with Docker and manage workloads using Kubernetes for robust, scalable deployments.
Observability & Monitoring
End-to-end visibility with tools like ELK, Prometheus, Grafana, Loki, and Graylog — ensuring uptime, performance, and fault detection.
Automated Infrastructure Management
Infrastructure-as-Code (IaC) setups and automation to provision, scale, and update systems with minimal manual intervention.
Database Optimization
Tune SQL, NoSQL, and Vector DBs for real-time AI workloads.
Frequently Asked Questions
Learn more about our platform and our approach to building fractional AI teams.
How does Superteams.ai differ from traditional MLOps consulting or hiring?
We provide fractional, on-demand MLOps teams, meaning you get senior experts for exactly the duration and scope you need, without long-term hiring costs. We augment your in-house capabilities, managing the ML lifecycle from start to finish.
Can your teams work with our existing infrastructure?
Yes. Superteams specializes in seamless integrations across cloud, on-prem, and hybrid setups. Whether you’re on AWS, GCP, Azure, or private infrastructure, our teams ensure frictionless deployments with minimal disruption.
Do you support Sovereign AI and data privacy requirements?
Absolutely. All deployments can be fully contained within your infrastructure (cloud or on-premises), so your AI models, data, and proprietary IP stay under your control, aligned with security and compliance needs.
What parts of the ML workflow do you manage?
We can ensure data security and compliance by deploying open weight LLMs within secure cloud infrastructure or fully private environments. For businesses handling sensitive data like patient records, we can leverage self-hosted models that operate within a controlled setup, eliminating external data exposure. The AI agents can be deployed on private cloud, on-premise servers, or air-gapped environments, ensuring compliance with HIPAA, GDPR, and other regulations. Data ingestion, processing, and retrieval occur within your infrastructure, with no leakage to external AI platforms.