Cut Azure waste and automate one painful workflow.

I help Azure-based teams reduce cloud spend, remove repetitive manual work, and ship production-ready AI agents. Fixed-scope. Async-only. Zero meetings.

48-hour turnaroundSnapshot needs no credentialsZero meetingsMicrosoft Certified Cloud Architect

20-45%

Azure spend cut

Benchmarked across audits

2-4 wk

First pilot shipped

AI agent to production

30+

Systems delivered

Production-grade

Certified

Cloud Architect

Microsoft Azure, 2024

How It Works

Three steps. Zero meetings.

01

Snapshot

Share your Azure export or describe the workflow bottleneck. You get a baseline report in 48 hours. Free.

02

Prioritize

I send back a focused recommendation with the biggest wins, likely impact, and a fixed-scope implementation path.

03

Ship

Async delivery in 1-4 weeks. You get the implementation, a runbook, dashboards, and a follow-up review.

What You Get

Fixed scope. Clear deliverables. No retainers.

Free Azure Snapshot

$0

48 hours

A fast analysis of your Azure spend, workflow friction, or automation opportunity. No credentials required. No meeting needed.

  • Identifies idle resources and spend waste
  • Surfaces the highest-ROI automation target
  • Includes a prioritized recommendation
Get Free Snapshot

Implementation Sprint

$2,000-$5,000

1-4 weeks

A fixed-scope sprint to remove one bottleneck: cut Azure waste, automate a workflow, or ship an AI agent. Ships with AgentGuard cost controls built in.

  • Fixed scope, fixed price, async delivery
  • Production deployment with runbook
  • AgentGuard runtime budget enforcement included
Start a Project

Workflow Audit

$200-$500

5 business days

A prioritized automation roadmap with ROI estimates for every workflow your team runs manually.

  • Each workflow scored by hours wasted and ROI
  • Specific recommendations for what to automate first
  • Written deliverable, 100% async
Get an Audit

Proof

What a sprint looks like

AgentGuard -- AI Agent Cost Control

agentguard47.com

Problem

AI agents running overnight experiments were burning through API budgets with no visibility or enforcement. A single runaway loop could consume an entire month's budget in hours.

What Changed

Built AgentGuard -- an open-source Python SDK that enforces hard budget, token, time, and rate limits on any AI agent at runtime. Integrated an MCP server so agents can query their own operational metrics in real time.

Stack

Python, MCP protocol, PyPI, Claude/GPT APIs

Timeline

Ongoing (245 commits, 6 releases)

Outcome

Now bundled into every client AI agent deliverable. pip install agentguard47. Zero runaway cost incidents since deployment. Used as the cost control layer for the autonomous ML research agent (100+ experiments, 25% model improvement).

FAQ

Common questions

Patrick Hughes

Patrick Hughes

AI & Azure Engineer

Nashville, TN

Microsoft Certified Cloud Architect (Azure Solutions Architect Expert, 2024). I build AI agents, optimize Azure infrastructure, and automate workflows for teams that want results without meetings.

PythonAzureNext.jsAI Agentsn8nFastAPIDevOpsML Pipelines
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Ready to find out where your Azure spend leaks?

Free snapshot. No credentials. Results in 48 hours. No meetings required. No bloated consulting process. Just a focused review and a clear next move.