AWS Cloud Services
The infrastructure your AI systems run on -- built by engineers who’ve been on AWS since before SageMaker existed
AWS Done Right
Every AI system runs on infrastructure. The model gets the credit, but the GPU cluster, the data pipeline, the serving layer, and the monitoring stack are what determine whether it works in production or just in a notebook. We've been building on AWS since 2008, long enough to know which services deliver and which ones are just shiny distractions.
We build the AWS infrastructure that makes AI systems production-ready. SageMaker pipelines that actually retrain on schedule. Bedrock integrations that stay within budget. GPU clusters that release capacity when training finishes. No architectural astronautics, just infrastructure that works while your team focuses on the models.
Our AWS Services
AI-Ready Cloud Architecture
We design infrastructure for what your AI systems actually need: GPU instance selection, model serving topology, data pipeline throughput. If your workload fits on a single p5.48xlarge, we won't sell you a multi-region cluster.
ML Pipeline Engineering
SageMaker pipelines that take models from notebook to production without the usual six months of glue code. Training jobs, hyperparameter tuning, model registry, endpoint deployment -- all versioned and reproducible.
Infrastructure as Code
AI infrastructure changes fast. Your GPU clusters, training pipelines, and model endpoints should be in version control, reproducible, and teardown-safe. We use Terraform or CDK, whichever your team can maintain.
Serverless & Bedrock Integration
Bedrock gives you foundation models without managing infrastructure. We build serverless AI applications on Lambda and Bedrock that scale to zero when idle and handle burst inference without provisioning headaches.
GPU Compute & Container Orchestration
Training on P5 instances, inference on Inf2, batch jobs on spot GPUs. ECS or EKS with proper GPU scheduling, node affinity, and auto-scaling that actually releases expensive instances when they're idle.
MLOps & AI DevOps
CI/CD for models is different from CI/CD for code. We build pipelines that version datasets, track experiments, gate deployments on evaluation metrics, and roll back models that drift. Boring deploys, even for AI.
AWS Services We Use
AI & ML
- SageMaker
- Bedrock
- Comprehend
- Rekognition
- Textract
- Kendra
GPU Compute
- P5 Instances
- Inf2 Instances
- Trn1 Instances
- ECS
- EKS
- Batch
Data & Storage
- S3
- EFS
- FSx for Lustre
- Aurora
- DynamoDB
- OpenSearch
Networking
- VPC
- CloudFront
- API Gateway
- EFA
- PrivateLink
- Transit Gateway
Security
- IAM
- Cognito
- KMS
- WAF
- Macie
- GuardDuty
Monitoring
- CloudWatch
- SageMaker Monitor
- X-Ray
- Config
- EventBridge
- CloudTrail
Why AWS?
GPU Availability Across Regions
GPU capacity is scarce and unevenly distributed. We know which regions have P5 and Inf2 availability, how to use capacity reservations, and when spot instances make sense for training jobs.
AI-Grade Security
Model weights are intellectual property. Training data has compliance implications. We configure VPCs, encryption at rest and in transit, IAM boundaries, and data access controls built for AI workloads from day one.
AI Cost Control
GPU instances burn money fast. A forgotten p5.48xlarge costs over $98/hour. We set up spot instance strategies for training, auto-scaling inference endpoints, and alerts that catch runaway costs before they become budget emergencies.
Elastic AI Infrastructure
Training needs GPUs for hours, then nothing. Inference traffic spikes unpredictably. We build infrastructure that scales GPU compute up for training runs and scales inference endpoints down to zero between requests.
Why Choose Convective?
Certified and Experienced
Our architects have AWS certifications, yes, but more importantly, they have years of production experience. Certifications prove you can pass a test. We've handled actual outages.
Bills You Can Explain
We've cut AWS bills by 30-50% for clients who were over-provisioned. More importantly, we set up tagging and reporting so you know where your money goes.
Ongoing Support If You Need It
Some clients want us to hand over the keys and walk away. Others want 24/7 managed services. We're fine with either. Your infrastructure, your call.
Compliance Without Drama
HIPAA, PCI DSS, SOC 2, FedRAMP: we've built compliant architectures in each. We handle the technical controls; you handle the paperwork. It's a good division of labor.
Trusted by Industry Leaders
Let’s Talk About Your AI Infrastructure
Tell us what you’re building and what’s blocking production. We’ll give you a straight answer on the right AWS architecture for your AI workload -- and whether you actually need those GPU instances.