Revenue & Growth · Use Case Hub
Automate Paid Media Operations with AI.
How to automate paid media operations with AI across 0 industries with a scoped engagement page. Workflow design, AI agents, governance, and the KPIs (ROAS, CAC, creative velocity, budget waste, and time to insight) we report on weekly. Pick your industry below.
Projects from $15k · Refundable 7 days · Kickoff within 5 days
Primary outcome
improve campaign learning speed and creative throughput
What we ship
campaign analyst, creative testing backlog, reporting system, and optimization playbooks
KPIs we report on
ROAS, CAC, creative velocity, budget waste, and time to insight
What "automating paid media operations with AI" actually means
Automating paid media operations with AI is not a single product you buy. It is a workflow you redesign around AI as the operating layer. The agent handles the high-volume, high-structure tasks. Humans handle edge cases, exceptions, and trust-sensitive decisions. The system is instrumented to measure ROAS, CAC, creative velocity, budget waste, and time to insight and improve weekly.
What changes by industry is the systems the agent integrates with, the data it retrieves over, the controls it operates under, and the KPIs it has to defend. The architecture is similar; the integration and the controls are different.
The architecture we use for AI paid media operations
- Frontier LLM — Claude, GPT-4-class, or Gemini. We benchmark candidates on a labelled test set during Discovery.
- Retrieval layer over your approved internal sources, with source citations on every output.
- Tool use for reads and writes against your operational stack (CRM, ERP, ticketing, data warehouse).
- Reviewer queue for low-confidence outputs. Confidence thresholds set per workflow.
- Evaluation harness — labelled test set, weekly accuracy reports, regression alerts.
- Versioned prompts and reviewer-action audit logs for traceability.
0 industries with a scoped engagement page for paid media operations. Each is a dedicated build with industry-specific systems, controls, and pricing.
How do you automate paid media operations with AI?+
We map your existing paid media operations workflow, identify high-volume and high-structure tasks, build an AI agent that handles those tasks, and route low-confidence cases to a human reviewer. The build connects to the systems your industry already runs on, runs against a labelled test set, and ships behind a reviewer queue before it sees production traffic. We measure ROAS, CAC, creative velocity, budget waste, and time to insight from day one and improve weekly.
What is the best AI agent for paid media operations?+
There is no single off-the-shelf "best" agent for paid media operations — the right architecture depends on the systems and data of your industry. We typically combine a frontier LLM (Claude, GPT-4-class, or Gemini) with a retrieval layer over your approved sources, tool-use for your stack, and a reviewer queue. We benchmark candidates against a labelled test set during Discovery and pick the model with the best accuracy/cost ratio.
What does AI paid media operations cost?+
Three phases, billed separately. Discovery sprint: $5k. Build engagement: $15k–$22k. Run retainer: $2k–$3k / mo. ~$25k–$45k typical year 1 (60% take the run option for ~6 months). Pricing varies slightly by industry — see the industry-specific pages below.
How long does it take to deploy AI paid media operations?+
Thin-slice in production in ~6 weeks after Discovery, full Build phase over 6-8 weeks. By day 90, ROAS, CAC, creative velocity, budget waste, and time to insight is instrumented and you have a baseline against which to expand to adjacent workflows.
Which industries do you build AI paid media operations for?+
0 industries listed below have a scoped engagement page for paid media operations, each with industry-specific systems, controls, and KPIs. Common starting industries include , and others. Don't see yours? We build for any sector — tell us about your workflow and we'll scope it.
What do we own, and what do you own?+
We own workflow design, prompts, retrieval architecture, evaluation harness, and weekly improvement. You own data access, policy, exception approval, and final commercial decisions. At the end of the engagement, every prompt, eval, and config is handed over — no lock-in.
Selected portfolio
Real builds tied to paid media operations
A rotating selection of engagements where paid media operations was a primary driver, drawn from our active portfolio. Sectors and scope are accurate; client identities are withheld under engagement NDAs.
Q1 2026
Premium marketing site for a specialist detailing workshop
Premium vehicle care specialist · DACH region
Marketing site for a premium vehicle detailing workshop: ceramic coating, paint protection film, detailing, smart repair. Luxury automotive visual direction, structured per-service catalog with proof points, German-market SEO foundation, appointment-oriented CTAs throughout the funnel.
- Next.js + custom design system
- Core Web Vitals first
- German-market SEO
Q3 2025
On-demand regional aviation booking — flexible flight network across smaller cities
Regional aviation operator · DACH
Booking and operations stack for an on-demand regional aviation network connecting secondary cities. Customer-facing booking flow with dynamic availability, operator-side dispatch tools, route economics dashboards. Designed for a sustainable flight-network operating model rather than fixed-schedule airline patterns.
- Next.js + native-app companion
- Dynamic availability engine
- Operator dispatch console
Q3 2025
Specialist trades marketing site — roof, facade, renovation services
Construction trades specialist · France
Marketing site for a regional roofing and facade specialist: service architecture covering roof renovation, facade work, and installation services; quote-request workflow with regional catchment routing; SEO foundation built for local intent across nearby municipalities.
- Next.js + responsive
- Local SEO foundation
- Quote-request workflow
Client identities withheld under engagement NDAs. Sector, geography, and scope are accurate. Full case studies on request.