Four practice areas. One goal: making your cloud environment secure, efficient, and ready for what comes next.
Cloud Infrastructure & Architecture
We design and implement production-grade AWS environments — from single-account setups to multi-account, multi-region architectures supporting $300K+ monthly cloud spend.
Multi-account AWS architecture with Organizations and Control Tower
We implement the guardrails and controls that keep regulated workloads secure and auditable — across healthcare, pharma, financial services, and beyond.
We build data pipelines that scale and AI systems that deliver measurable business value — from real-time streaming to generative AI with enterprise guardrails.
Data lake architecture and real-time streaming pipelines (Kinesis, Glue, EMR)
ML model training and deployment (SageMaker, GPU-accelerated PyTorch)
Generative AI integration (AWS Bedrock, Claude, RAG pipelines)
Vector databases and semantic search (OpenSearch, Pinecone, Milvus)
Real-time inference endpoints and prediction streams
A structured, repeatable approach that reduces risk and delivers results.
01
Assess
We audit your current infrastructure, identify gaps in governance, security, and cost efficiency, and document findings with detailed architecture diagrams.
02
Architect
We design the target state: account structure, networking, compliance controls, data pipelines, and automation. Everything is documented and reviewed before a single resource is provisioned.
03
Automate
We implement using Infrastructure-as-Code, build CI/CD pipelines, deploy monitoring and alerting, and deliver comprehensive documentation. Then we train your team to operate it independently.
Selected Engagements
Representative projects across industries. Client names withheld per NDA.
Media & Entertainment
Challenge
Client building a mobile media platform needed a content moderation pipeline and a custom recommendation engine with signal ingestion from user interactions.
Solution
Kinesis-to-S3 signal pipeline with Glue ETL for interaction data
SageMaker recommendation model with OpenSearch vector DB
Full infrastructure provisioned via AWS CDK
Parallelized moderation pipeline reduced processing from 4–6 minutes to under 30 seconds.
Insurance
Challenge
Legal team manually reviewing 5% of incoming law firm bills for contract compliance, missing overbilling across the remaining 95%.
Solution
Claude 3.5 Sonnet via Bedrock for automated contract rule extraction
Textract for PDF processing of legal invoices
Lambda + Step Functions orchestration for bill compliance verification
Flask web UI for human review. All Terraform-provisioned.
Now automatically reviews 100% of incoming legal bills in real-time. Infrastructure is serverless; cost of inference is immaterial compared to savings.
Pharma
Challenge
Client needed daily inventory of all AWS resources across 100+ accounts for compliance verification with automated remediation.
Solution
Python application with plugin architecture as Step Functions state machine
