AI Infrastructure & Deployment
Ship AI to production. Scale it without surprises.
Building a great model is only half the problem. Getting it to production reliably — with low latency, high availability, cost control, and zero vendor lock-in — is where most teams struggle. We've deployed AI infrastructure for 480+ projects.
What we deliver
Every engagement is scoped, priced, and delivered against these capabilities.
Model Serving Infrastructure
GPU-optimised serving with vLLM, TGI, or Triton. Batching, quantisation, and caching strategies that cut inference cost by 60–80%.
Private Cloud & On-Premise
Deploy models on your own cloud account or on-prem hardware. Full data residency, no third-party API dependency.
MLOps & CI/CD
Automated training, evaluation, and deployment pipelines. Model registry, versioning, and rollback in one command.
Observability & Cost Control
Inference latency, token usage, error rates, and cost-per-query dashboards. Automatic alerting and budget caps.
Auto-Scaling
Kubernetes-based auto-scaling that handles traffic spikes without over-provisioning. GPU node pools with spot instance optimisation.
Security & Compliance
VPC isolation, encryption at rest and in transit, audit logging, and AWS Certified compliant deployment patterns.
How we work
A predictable process that keeps you informed and in control at every stage.
Infrastructure audit
Review your current serving setup, cost structure, latency requirements, and compliance constraints.
Architecture design
Design serving stack, scaling strategy, monitoring, and CI/CD pipeline.
Build & benchmark
Deploy infrastructure, run load tests, optimise for latency and cost.
Handover & documentation
Full runbook, monitoring dashboard, and knowledge transfer to your team.
Technologies we use
Serving
Orchestration
MLOps
Monitoring
Is your AI infrastructure production-ready?
We'll review your current setup and identify the risks before they become incidents.
Response within 24 hours. NDA available on request.