Capability 07
AI Infrastructure & AIOps
Build and operate the infrastructure powering enterprise AI.
Services included
- AI infrastructure architecture
- GPU and cloud infrastructure optimization
- Model deployment and serving
- Inference optimization
- AI gateway integration
- Scalability and reliability engineering
- AI infrastructure monitoring
- Automated operations
- Cost and resource optimization
- Disaster recovery
Business problems addressed
- Inference cost or latency that makes an otherwise good system unusable.
- A deployment path that cannot scale, recover, or be observed.
- Infrastructure frozen around a single demo environment.
Example enterprise use cases
- Serving a model inside a measured latency and cost budget.
- Designing cloud and GPU footprint around a real workload.
- Adding monitoring, scaling, and a recovery path before broad rollout.
Typical deliverables
- Infrastructure architecture.
- Deployment, serving, and gateway setup.
- Cost and performance review.
- Operating monitors and a disaster-recovery plan.
Engagement model
Project-Based Implementation or a Dedicated AI Engineering Team