AdGent is an AI-powered ad management platform that automates 90% of your paid media work across Google Ads, Meta, LinkedIn, and other major advertising channels. We've spent years inside paid media accounts — managing budgets, testing creative, explaining to clients and managers why the same campaign could work beautifully one week and crash the next.
The work can be exciting, but it's rarely sustainable.
Most of what passes for "strategy" in advertising today is actually operational noise — tiny adjustments made to keep platforms happy rather than audiences engaged.
We built AdGent to change that.
The problem isn't skill — it's bandwidth
Every marketer knows what great looks like: clarity in creative direction, clean audience segmentation, meaningful testing, and consistent learning loops.
The problem is never knowing what to do. It's having the bandwidth to actually do it.
Platforms generate mountains of data, but they also demand constant supervision. Budget pacing, fatigue management, bid fluctuations, attribution weirdness — it all eats into the time marketers should spend thinking.
The result is a profession full of talented people forced into reactive patterns: refreshing dashboards, pulling reports, adjusting levers.
AdGent exists to get marketers out of that loop.
What AdGent does
At its simplest, AdGent is an autonomous agent that manages the operational layer of paid media — the work that needs to be done precisely, constantly, and without ego.
It connects directly to your ad platforms, reads performance data in real time, and takes calibrated actions where they'll have the most impact.
- Budget allocation: It moves spend between campaigns, ad sets, or even platforms based on live efficiency data — no waiting for weekly reviews.
- Bid optimization: It adjusts bids to keep your spend efficient even when auction dynamics shift.
- Creative rotation: It detects when an ad starts to fatigue and replaces or recommends better-performing alternatives.
- Signal analysis: It distinguishes between genuine performance trends and random variance, so you act on the right data — not the loudest.
- Pacing and delivery control: It keeps daily and lifetime budgets in balance without constant human oversight.
The point isn't to automate marketing. It's to remove the overhead that prevents marketers from doing real marketing.
How it works under the hood
We built an MCP (Model Context Protocol) for Ads — a bridge between advertising platforms and intelligent agents.
It connects directly to Google Ads, Meta, LinkedIn, and other major channels, exposing live campaign data through a structured protocol that AdGent — and our other AI agents — can understand and act on.
The MCP layer turns complex account data into a shared, queryable context. It allows our AI agents to access:
- Campaign and ad set information
- Performance metrics (spend, ROAS, CPA, CTR, etc.)
- Keyword and audience analytics
- Creative-level performance signals
- Budget and pacing data
On top of this infrastructure, we built AdGent — an AI agent that uses the MCP to analyze performance, surface insights, generate recommendations, and manage ads automatically.
AdGent doesn't just read metrics; it interprets them in context, identifies opportunities for improvement, and can execute actions across connected platforms — reallocating spend, rotating creative, or adjusting bids based on real-time data.
Together, MCP for Ads and AdGent form a complete intelligence layer for modern performance marketing: the protocol provides context and structure, and the agent applies reasoning and action.
What changes when teams work with AdGent
When AdGent takes over the repetitive tasks, teams stop reacting to numbers and start thinking about meaning. Instead of wondering why CTR dipped yesterday, they're able to ask whether the message still resonates. Instead of comparing CPC across ad sets, they're thinking about channel mix and audience intent.
That's what we mean by "effectiveness." It's not about doing more work faster — it's about doing the right work, with more clarity and less noise.
We didn't build AdGent because we wanted to automate ad buying. We built it because we were tired of seeing great marketers lose their edge to busywork.
Every account review we've done over the years follows the same pattern: The most talented strategists are drowning in logistics — fighting for stable pacing, manually adjusting budgets, re-exporting the same data for the tenth time.
It's not a talent problem. It's a system problem. Humans are being used for what machines are better at, and vice versa.
AdGent flips that. It lets machines handle precision, so humans can handle perspective.