We build quiet infrastructure for systems that have to keep running.

DevOps, AI tooling, ML training, and cloud operations for federal and commercial teams. Small senior squad. Production-grade work.

What we deliver → Start a conversation
●DevSecOps●AWS / Azure / GCP●Kubernetes · ECS · EKS●Terraform · Terragrunt●CI/CD Pipelines●AI/ML Platforms●SRE · Observability●FedRAMP · CMMC●Cloud Cost Optimization●Zero-downtime Migrations ●DevSecOps●AWS / Azure / GCP●Kubernetes · ECS · EKS●Terraform · Terragrunt●CI/CD Pipelines●AI/ML Platforms●SRE · Observability●FedRAMP · CMMC●Cloud Cost Optimization●Zero-downtime Migrations
/ capabilities

Infrastructure first. Everything else stacks on top.

Best-in-class infrastructure is the foundation. AI, data, and compliance layers are built on a platform that already runs cleanly.

foundation
01

Infrastructure & Platform

Multi-account cloud orgs. Terraform from day one. Container platforms, networking, identity. Blue/green, canary, pipelines with rollback.

stack
  • Terraform · Terragrunt · CloudFormation
  • EKS · ECS Fargate · AKS · GKE
  • ALB · NLB · CloudFront · Route53 · ACM
  • GitLab CI · GitHub Actions · CodePipeline
  • AWS Organizations · SCPs · Control Tower
on top
02

AI Tooling, Apps & MCP

Internal copilots, RAG, document intelligence. MCP servers for tool-use and agents. LLM gateways so swapping models doesn't break the app.

stack
  • Bedrock · Azure OpenAI · OpenAI · on-prem
  • MCP servers · agent orchestration
  • LangChain · LlamaIndex · pgvector · Pinecone
  • RAG · fine-tuning · eval pipelines
  • Prompt patterns · AI-assisted dev workflows
on top
03

Data & ML Pipelines

S3, lake formation, vector stores. Embedding pipelines with versioning. Streaming with Kafka, Kinesis, EventBridge. CDC when it actually matters.

stack
  • S3 · Lake Formation · Glue · Athena
  • Kafka · Kinesis · EventBridge · Pub/Sub
  • Postgres · DynamoDB · Redis · vector DBs
  • CDC patterns · data versioning
  • SageMaker · Bedrock · custom inference
around it
04

Observability & SRE

OpenTelemetry across the stack. SLOs that mean something. Runbooks that get used when it matters. Post-mortems that don't blame people.

stack
  • OpenTelemetry · Prometheus · Grafana
  • CloudWatch · X-Ray · distributed tracing
  • SLOs · error budgets · burn-rate alerts
  • Incident response · post-mortems
  • Chaos engineering when warranted
around it
05

LLM Access & Guardrails

LLM access behind a real gateway. BYOK, tenant isolation, audit logs. Prompt-injection defense beyond regex. Eval pipelines that catch model-swap regressions.

stack
  • Bedrock · Azure OpenAI gateways
  • BYOK · tenant isolation · audit logs
  • Prompt-injection defense · PII redaction
  • Eval pipelines · regression tests
  • Output validation · jailbreak mitigation
around it
06

Compliance & Guardrails

FedRAMP-adjacent. ATO documentation that passes review. SBOMs, supply chain hardening, secret scanning. Ship fast without slowing down.

stack
  • FedRAMP-adjacent · ATO docs
  • SAST · DAST · SCA · container scanning
  • SBOM · supply chain hardening
  • IAM least-privilege · SCPs · guardrails
  • CVE/CWE remediation · secret scanning
/ we know

Things we've shipped, broken, and fixed.

The short list of "we've actually done this in production, not in a deck."

infra
Stood up Control Tower landing zones. Migrated 200+ accounts into Organizations. Written Terraform modules that survive a re-org. Survived AWS region outages by designing for cell-based failure isolation. Know why your NAT gateway bill is too high and how to fix it without buying more commitments.
deploy
Blue/green, canary, progressive delivery. GitLab CI pipelines with proper rollback — not "redeploy and hope". Feature flags that don't leak state. Helm and Kustomize, both. ArgoCD and Flux, both. Know when not to use a sidecar.
compute
EKS, ECS Fargate, ALB ingress, IRSA, cross-AZ scheduling. Know when to pick Lambda vs Fargate vs a real cluster. Know why your pod is OOMKilled and how to fix it without just raising the limit. Know why "just run it on EC2" sometimes is the right answer.
ai dev
Built internal copilots that engineers use daily. RAG systems over 10M+ documents. Fine-tuned models that beat the baseline. Eval pipelines that catch regressions before users do. Know how to debug hallucination, not just talk about it.
ai apps
Built agent systems that take real actions on real systems. MCP servers for tool use. Bedrock and OpenAI behind a single gateway. Streaming responses, function calling, structured output, tool-use loops. Apps that real users depend on, not demos.
mcp
MCP servers for internal tools. MCP gateways for multi-tenant access. Auth, rate limiting, audit logging at the MCP layer. Know the difference between MCP and a function call — and when each is appropriate.
guardrails
Prompt-injection defense beyond regex. PII detection that doesn't break on names. Output validation against schema. Eval pipelines (LLM-as-judge, golden sets, regression tests). Know how to ship guardrails without blocking legitimate use.
compliance
ATO packages that pass review. SBOMs and supply chain hardening. CVE/CWE remediation under SLA. FedRAMP-adjacent practices without theater. Know what reviewers actually look for and how to ship without slowing down.
requirements
We turn vague business asks into technical specs that engineers can actually build from. Traceability from requirement → design → test → production. No "we'll figure it out as we go" — that just means rework later.
code
Python, TypeScript, Go, some Rust when warranted. We read code, write code, review code, and ship code. We don't just configure — we implement. The people on the sales call are the people who'd write your next module.
/ numbers

Some receipts.

1,500+
commits shipped in 16 months
500+
containers orchestrated
200+
cloud accounts stood up
79
projects delivered