Cloud architecture, AI strategy, and managed services across AWS, Azure, and Google Cloud. Built by senior engineers who stay until the work is done.
What We Do
We work across AWS, Azure, and Google Cloud, and every major AI platform. No vendor bias. Every engagement is led by senior engineers who recommend the right technology for the problem.
We design, build, and operate cloud environments across AWS, Azure, and Google Cloud. From landing zone architecture to multi-cloud strategy, we make sure your infrastructure is secure, performant, and cost-efficient on the right platform for each workload.
AWS · Azure · Google Cloud · Landing zones · Cloud migration · Hybrid & multi-cloud architecture · Monitoring & incident response · Disaster recovery
We help organizations retire technical debt and build cloud-native solutions that actually move the business forward. Our engineers bring years of hands-on experience with modern development practices across every major cloud platform.
Legacy migration paths · Cloud-native development · API design & integration · DevOps & CI/CD pipelines · Containers & Kubernetes · Serverless & microservices
We turn fragmented data into something your teams can actually use. Whether it's building a scalable data platform or deploying AI that solves real problems, we work across every major LLM and AI platform: OpenAI, Anthropic, Google, Meta, open-source models, and more.
Data platform architecture · Business intelligence · AI & ML solutions · LLM integration & fine-tuning · RAG & knowledge systems · Generative AI strategy
We optimize how your teams work. Whether your organization runs on Microsoft 365, Google Workspace, or a hybrid of both, we deploy and manage collaboration, identity, and productivity systems so your people can work securely from anywhere.
Microsoft 365 · Google Workspace · Collaboration architecture · Identity & access management · Endpoint management · Adoption & change management
We help organizations put AI to work on the knowledge and documents already buried in their systems. Whether it's permission-aware, source-cited answers surfaced through enterprise search, or a purpose-built application that extracts and structures data from complex documents, we build governed AI foundations that people can actually trust, on whichever platform fits your environment.
Enterprise search & retrieval (RAG) · AI agents & assistants · Document data extraction · Azure AI · AWS Bedrock · Google Vertex AI · Identity-aware governance
Your AI-built prototype works. Now make it enterprise-ready. We take vibe-coded applications (rapid builds from tools like Cursor, Copilot, and Claude Code) and harden them with proper architecture, security, testing, CI/CD, and operational readiness. The bridge between "it works on my laptop" and "it runs in production."
Architecture review & refactoring · Security hardening · Automated testing · CI/CD pipelines · Observability & monitoring · Production deployment
Our Method
We assess your current environment, map dependencies, and identify opportunities. Every engagement begins with understanding where you are and where the work needs to go.
We design solutions that follow cloud-native best practices and fit your goals. We recommend the right tool for the problem, not the one we're partnered with.
Our engineers build, migrate, and deploy. They work inside your environment and own the outcomes. Senior talent stays on through implementation, not just planning.
After go-live, we monitor performance, refine configurations, and reduce cost. The relationship doesn't end at deployment. We keep improving the environment alongside your team.
Selected Work
Real outcomes from recent engagements. These are representative of how we work and what we deliver.
Healthcare · AI & Compliance
A healthcare analytics firm needed AI capabilities against production claims data and DevOps pipelines, but HIPAA required per-user identity traced all the way to the data layer. Off-the-shelf tooling couldn't meet the audit bar. We built a multi-agent platform using Azure AI Foundry with custom MCP servers, OAuth passthrough forwarding each user's Entra token to every backend, and an immutable audit row for every tool call.
Every AI interaction audited to the individual user, queryable by the HIPAA security officer on demand
Per-user access controlled with a single database operation. Onboarding and revocation take seconds
Extensible foundation already being reused for new backend integrations
Legal · AI & Security
Attorneys at a mid-size firm needed AI for daily work: drafting documents, looking up colleagues, answering questions using internal firm knowledge. Commercial LLM products were off the table due to attorney-client privilege. We deployed a private AI assistant on Azure, routing all inference through the firm's own tenant boundary with Foundry, backed by RAG over Azure AI Search and custom MCP services for document generation and directory lookup.
Firm data never leaves the Azure tenant. Full attorney-client privilege preserved
Single Entra SSO for every attorney with complete activity audit via Application Insights
All infrastructure in Terraform with full environment parity from dev through production
Contact
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