// CASE STUDY
AI GOOGLE ADS
AUTOMATION
An automated research-to-launch system that distills competitive intelligence into policy-safe, highly optimized Google Ads campaigns, saving agencies up to 95% of setup time.
- LangChain
- Python
- Node.js
- Next.js
- Supabase
- PostgreSQL
- Google Ads API
- SerpApi
- Gemini
- Satori
- Resvg
// THE PROBLEM
MANUALSETUPDOESN'T SCALE.
Marketing agencies running Google Ads for multiple clients face an operational bottleneck that has nothing to do with strategy, it's the hours of repetitive labor before a single ad serves.
For every new client campaign, an account manager spends 13 to 25 hours on competitive research, ad copywriting, display creative production, campaign assembly, and policy review.
“Agencies either limit their client count, hire junior staff who make policy mistakes risking account suspensions, or cut corners on research producing generic ads.”
// WHAT WAS BUILT
RESEARCH-TO-LAUNCHCO-PILOT.
This system automates the entire front half of Google Ads management while keeping humans in control of strategy, budgets, and the publish button.
Competitive Analysis
Scrapes and analyzes 100+ competitor ads, ranking angles by longevity to find proven strategies and gap opportunities.
- SerpApi
- Longevity Ranking
- Gap Analysis
Variant Generation
Generates gap-first Search RSA headlines and descriptions, strictly adhering to character limits and insight-derived strategies.
- Deterministic Padding
- Insight Mapping
Display Creative Generation
Uses structured render-specs to generate Display ads automatically into 7 standard sizes without the LLM ever writing layout HTML/CSS.
- Satori
- Resvg
- Dynamic Scaling
// SAFETY & ARCHITECTURE
NON-NEGOTIABLECONSTRAINTS.
The system relies on a LangChain Python service and a Next.js dashboard, communicating to a Supabase Postgres database. Safety is designed into the core architecture.
Deterministic Budgeting
The LLM never sets or modifies budgets. Budget values flow deterministically from the client profile and are hard-capped at every layer.
- Hard Capping
- Strict Execution
Two-Layer Quality Gate
A deterministic policy scan checks for banned superlatives and terms. The LLM rubric critiques clarity, CTA strength, and differentiation.
- Compliance Gate
- Double Verification
Automated Campaign Assembly
Assembles ad groups, keyword distributions, and bid strategies automatically based on insights without human assembly time.
- Smart Defaults
- Token Distribution
Explicit Human Launch
The system never publishes on its own. Every campaign creation requires an explicit human review and approval action via a modal.
- Human in the Loop
- Configure by Exception
// THE ROI
AGENCY-LEVELIMPACT.
The system doesn't just save time, it changes the agency's unit economics. Adding clients 7-25 is pure margin without a new hire needed.
95% Less Labor
Campaign setup drops from 13-25 hours per client down to 30-60 minutes, consisting mostly of quick human review.
Exponential Capacity
Account managers can scale from 5-8 clients up to 25-40 without sacrificing ad quality, unlocking pure margin.
Insight-Driven Ads
Unlike generic AI copywriting tools, every ad variant is grounded in competitive intelligence and longevity data.
// OUTCOMES
RESULTS.
// LET'S TALK
WANT RESULTSLIKE THIS?
We scope everything in detail before payment is taken. You work directly with a senior engineer, not a project manager relaying messages to an offshore team.