Cloud Infrastructure
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VMG Systems |
Technical Consulting & Clean Slate Engineering

We eliminate complex technical debt, strip unmanaged infrastructure, and ship production-ready, fully observable architectures using our Clean Slate methodology.

Flagship Rebuild Case Study: Automotive Voice AI Platform Rebuild — complete full-stack refactor, migrating high-latency legacy services to a 5-service monorepo with sub-second API latency, 100% Terraform coverage, and a 99.5% uptime SLA. Read the case study →

ENGINEERING CAPABILITIES

Services Overview

AI Integration & Data Pipelines

Your data is already valuable. I build the highly resilient pipelines, retrieval layers, and semantic storage engines that make it useful to Large Language Models in production.

  • Vector Database implementation (PostgreSQL/pgvector, Qdrant)
  • Structured output workflows via Gemini Pro, Claude 3.5, and OpenAI
  • High-speed semantic caching (Redis) and embedding generation
  • Automated prompt evaluation (Evals) and Golden Dataset benchmarking

Cloud Infrastructure & Modernization

I replace manual cloud configuration and fragile infrastructure with robust, Terraform-managed, reproducible deployments. GCP and AWS engineered to standard, with zero ClickOps allowed.

  • 100% Terraform-codified GCP and AWS infrastructure
  • Secure zero-trust site-to-site networking via Tailscale
  • VPC Service Controls and Workload Identity Federation
  • Multi-environment deployment workflows (Dev/Staging/Prod)

Custom Platform & API Engineering

High-throughput asynchronous Python (FastAPI) backends and accessible Next.js dashboards / React Native frontends built around strict typed standards.

  • Async FastAPI backends with Pydantic structured schemas
  • React Native mobile apps with native offline/background persistence
  • High-performance Next.js admin & telemetry web dashboards
  • Full end-to-end type safety across the entire engineering stack

VMG SYSTEMS

The Clean Slate Protocol

Most engineering platforms fail because of architectural foundation choices, not because of coding skills. We establish rigorous discipline across four core parameters to ensure that what we build thrives on complexity.

Methodology Focus

  • Unified Monorepo Architecture:Consolidating services into a single context. This allows developers and advanced AI coding agents to have full context across UI layers, database definitions, and pipeline workflows, drastically speeding up velocity.
  • Zero-ClickOps Infrastructure (IaC):No configuring things in browser consoles. Every cloud database, firewall rule, storage bucket, or API service account is strictly codified in Terraform. This ensures security, repeatability, and instant environments tear-down.
  • Strict Plan → Act → Validate Loop:Every single feature deployment is designed as a modular spec. No manual commands, no raw hacking in live environments. Every step is automated, evaluated, and validated prior to merge.
  • Inference Regression Testing:We build eval dataset baselines on Day 1. Every model tweak or prompt adjustment is evaluated against test baselines before shipping, ensuring that prompt drift does not degrade user UX.

Technical Standards

01 / Network & Security
Workload Identity Federation, zero shared secret keys in source repos, and secure site-to-site tunnels via Tailscale zero-trust.
02 / Backend Execution
Async Python (FastAPI Engine) with strictly validated Pydantic models for highly predictable structured outputs.
03 / User Interface
Modern, accessible (WCAG 2.2 AA standards), type-safe reactive systems built with Next.js App Router and React Native.
04 / Observability Gateway
Full execution trace telemetry wrapping LLM requests via Langfuse, capturing input, outputs, latency, tokens, and accurate cost metrics on Day 1.

Production Observability on Day 1

Langfuse telemetry is running before your first customer feature ships. Every LLM call, prompt completion, and database fetch is fully traced. When something fails or experiences high latency, you receive slack alerts detailing the exact root cause before users notice.

HOW TO WORK WITH VMG SYSTEMS

Flexible Engagement Tiers

Choose the engagement layout that aligns with your timeline, budget, and business constraints. All models strictly enforce the VMG Clean Slate methodology.

Diagnostic
1 - 2 Weeks

Fixed-Scope Audits

Comprehensive diagnostic of your existing repositories, cloud setup, and AI pipeline bottlenecks.

Key Deliverables:
  • Detailed ClickOps inventory & uncodified asset catalog
  • AI inference costs, prompt engineering, & observability assessment
  • Vulnerability assessment & VPC security analysis
  • Complete remediation blueprint & step-by-step rebuilding roadmap
Development
4 - 6 Weeks

Custom Product Sprints

Greenfield, clean-slate production builds of core APIs, backend platforms, or mobile components.

Key Deliverables:
  • 100% Terraform-managed GCP/AWS infrastructure
  • Async FastAPI backend with structured Pydantic data schemas
  • Next.js web dashboard or React Native client implementation
  • Full Langfuse observability, telemetry, and error tracking out-of-the-box
Advisory
Monthly Retainer

Fractional AI/Data Lead

Ongoing, embedded leadership providing high-leverage guidance for your engineering and data teams.

Key Deliverables:
  • Architecture, data governance, and AI pipelines design advisory
  • Implementation of automated CI/CD and secure container workflows
  • Prompt caching, evaluation datasets, and semantic caching optimization
  • Continuous optimization of infrastructure costs and platform reliability

Ready to rebuild?

Let's stop fighting complexity and configure an architecture that thrives on it.

Reach out to schedule a diagnostic session. Tell us what is broken in your current cloud setup or AI pipeline, and we will formulate a clean-slate roadmap to resolve it.

Initiate Consultation

Diagnostic audits have limited availability. Secure your Q3 2026 onboarding slot.

Get In Touch