Services
AI Platform & MLOps
Build infrastructure for deploying, serving, evaluating and operating machine-learning and generative-AI workloads in production.
The problem
AI experimentation and production AI are different engineering problems. Prototypes stall when serving, GPUs, rollout safety, and observability are treated as afterthoughts.
What TEDEAS does
TEDEAS designs the platform layer that takes models and AI applications from a notebook or demo into a dependable production environment — without turning the engagement into a data-science project.
Capabilities
- Kubernetes-based AI platforms
- Model serving infrastructure
- LLM inference infrastructure
- GPU workload orchestration
- MLOps pipelines
- Production model deployment
- Rollout and rollback strategies
- Canary and shadow deployments
- AI observability
- Evaluation infrastructure
- Platform integration
Need experienced engineering capability?
Talk to TEDEAS about your cloud, platform, reliability or AI infrastructure initiative.
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