Fully managed. Fully yours.
Infrastructure Setup
We design and deploy your entire AI infrastructure from scratch — VPCs, IAM, compute, storage, and networking.
Ongoing Management
24/7 monitoring, patching, scaling, and cost optimisation. We handle the infrastructure so your team focuses on models.
Cost Optimisation
Spot Instances for training, Savings Plans for inference, and rightsizing recommendations updated monthly.
Security & Compliance
Encryption at rest and in transit, VPC isolation, IAM least-privilege, and compliance with HIPAA, GDPR, and SOC 2.
Every layer of your AI stack, covered.
GPU & Compute Optimisation
Right-size your GPU instances (P3, P4, G5), implement Spot Instance strategies for training, and optimise inference costs with Inferentia and Graviton.
SageMaker MLOps Pipelines
End-to-end ML pipelines from data ingestion to model deployment. Automated retraining, A/B testing, and model registry management.
Bedrock Infrastructure
VPC endpoints, IAM roles, Knowledge Base setup, and Guardrails configuration for secure, production-grade Bedrock deployments.
Vector Database Management
Amazon OpenSearch Serverless, pgvector on Aurora, and Pinecone integrations for RAG pipelines and semantic search.
Data Pipeline Architecture
AWS Glue, Kinesis, and EventBridge pipelines that feed clean, structured data to your AI models in real time.
AI Observability
CloudWatch dashboards for model latency, token usage, error rates, and cost per inference. Alerts before issues impact users.