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AI & Agents2026Live

Fix Eletros – AI-assisted Google Ads operations loop

Remote heartbeat, vault-based account memory and an offline-conversion-ready foundation

AI-assisted operating system for Google Ads at Fix Eletros/Fogoes, with recurring syncs, a live dashboard, an execution queue and a future path linking WhatsApp, service orders and revenue.

Quick summary
Role
Automation architect, growth systems builder & technical operator
Core stack
Node.js · JavaScript · Google Ads API · Railway Functions
Talk about a similar project
Type
AI & Agents
Status
Live
Role
Automation architect, growth systems builder & technical operator

Context and objective

AI-assisted operating system for Google Ads at Fix Eletros/Fogoes, with recurring syncs, a live dashboard, an execution queue and a future path linking WhatsApp, service orders and revenue.

I set up a dedicated operating workspace for the Fix Eletros account, turning Google Ads optimization into a traceable loop with memory, heartbeat checks and guardrails. The system syncs campaigns, ads and recent signals into a living vault, then generates dashboards, audits, heartbeat deltas, action queues and automated RSA review flows. When AI is available, the agent layer produces operating summaries automatically. In parallel, I mapped the future offline-conversion architecture so optimization can move beyond conversation starts and toward scheduled service orders, completed jobs and confirmed revenue.

The challenge

The core challenge here was not just building a polished interface. It was designing a flow that fit the real business context, reduced operational noise and turned a fragmented process into something clearer, faster and more reliable.

That usually means aligning customer service, decision-making, record keeping, automation and follow-up under one coherent logic. In other words: making the product support the operation, not the other way around.

The solution

I set up a dedicated operating workspace for the Fix Eletros account, turning Google Ads optimization into a traceable loop with memory, heartbeat checks and guardrails. The system syncs campaigns, ads and recent signals into a living vault, then generates dashboards, audits, heartbeat deltas, action queues and automated RSA review flows. When AI is available, the agent layer produces operating summaries automatically. In parallel, I mapped the future offline-conversion architecture so optimization can move beyond conversation starts and toward scheduled service orders, completed jobs and confirmed revenue.

Daily Railway heartbeat consolidates snapshots, dashboards, audits and the action queue

The vault acts as the official memory and live operating context for the account

Safe process to test, publish, monitor and promote winning RSAs on D+3 and D+7

Agent layer generates automated operating summaries and heartbeat diffs when AI is enabled

Future offline-conversion architecture maps the path from conversation to service order to revenue

Real impact

The account runs on memory, heartbeat checks and a live action queue

RSAs move through a safer cycle of testing, review and promotion

The future architecture makes optimization by service order and revenue possible, not just conversation starts

Technology

Node.jsJavaScriptGoogle Ads APIRailway FunctionsObsidian VaultPowerShellGemini

My responsibilities

  • Designed the automation architecture and the operating loop
  • Implemented the main sync, worker, remote cron and vault artifact generation
  • Created guardrails to avoid blind automation inside a live media account
  • Designed the future attribution and offline conversion import pipeline

Final CTA

If you want to build something like this or reorganize an operation that still depends too heavily on manual work, overloaded customer service or a confusing interface, this is exactly the kind of project where I usually create the most value.