We had a dumb but nagging question.
Everyone's racing to use AI for advertising. But does AI actually understand an ad? Like, really understand it the message, who it's talking to, whether it's landing? Or is it just vibing and generating plausible-sounding words?
We couldn't find a benchmark that tested this. So we built one.
We took 108 real ads the kind you'd scroll past on Instagram or see on a billboard in Tokyo. Fashion, fintech, food, health, FMCG, D2C. USA, EU, Asia. Some with influencers, some without. The kind of messy, real-world creative that agencies actually deal with.
Hey Product Hunt! π
The average performance marketer spends 60% of their time on workflow β not strategy, not creativity, not results. Just moving things between tools.
That's 3 days of your working week. Gone. Every week.
Meta Ads Manager. Google Ads. A competitor spy tool. Canva. Your analytics dashboard. A spreadsheet tracking all of it. And somewhere in that chaos, you're supposed to write copy that actually converts.
We built ad-vertly for the marketer who's great at advertising but drowning in operations.
One conversation. Your entire ad operation.
Tell it your brand URL. It learns your voice, style, and audience instantly β no 47-step onboarding. From there:
π Intelligence β Spy on competitor ads across Meta, Google, TikTok, LinkedIn & Reddit ad libraries
π¨ Creative β Generate on-brand images, videos & copy in seconds. No Canva. No agency brief. No back and forth.
π Launch β Go live on Google, Meta, Taboola & Outbrain in plain English. Not "export and figure it out" β actually live.
π Optimize β Connect your analytics, e-commerce & social tools. Ask questions, get answers, take action β all in one conversation.
It's an AI agent that closes the loop from idea to live campaign β without you opening another tab.
We also ran an early stage test called Creative Reasoning Benchmark β ad-vertly scored 19.73/20, outperforming generic LLMs on message clarity, context understanding, and actionable ad improvements
We're not promising magic. We're promising the 3 days back.
Try it free β no credit card required π & 50 extra free credits for PH users
Drop your questions below, we're here all day.
@gaurav_singh91Β Thanks for letting me explore and test ad-vertly. Itβs exciting to see how thoughtfully itβs built. Reducing the back-and-forth between tools is a big win for marketers. Looking forward to watching this grow. Congratulations to the team on a strong early launch!
@charishma_puliΒ thanks
Congrats on your launch, man! ππ»
@npmitaartΒ Thanks
It has been a very humbling response from everyone we can not more proud
Congrats on the launch! Closing the loop from competitor intel to live campaigns in one conversation is a strong promise. How do you prevent over-automation from flattening creative differentiation? If many marketers rely on the same agent for insights and copy, what ensures campaigns donβt converge toward similar messaging and bidding strategies over time?
@vik_shΒ Viktor β this is the right thing to push on, and I'll be direct
The short answer is that the differentiation risk lives upstream of where ad-vertly operates
Here's why:
The brief is the moat. ad-vertly doesn't start from a generic template β it starts from your brand. The moment you mention your brand, it auto-extracts your colors, voice, positioning, and design rules into a brand profile that governs every creative output in the session. Two brands asking for the same ad type get fundamentally different outputs because the brand context is baked into the generation, not layered on top. The homogenization risk you're describing is higher when marketers skip brand-building entirely β ad-vertly actually reinforces the discipline of starting from a distinct identity.
Competitor intel is designed to surface white space, not replicate it. When your agent searches across Meta, Google, TikTok, LinkedIn, and Reddit ad libraries, the intent is to show you what's saturated so you can find the angle that isn't. The creative tools in ad-vertly β including audience roleplay and what we call "Break Creative Blocks" β are specifically built to generate non-obvious, unconventional concepts, not pattern-match to whatever's already running. The research output is yours to interpret; the agent surfaces signal, you make the strategic call.
On the optimization convergence question specifically: this one I'll be honest about. Any system optimizing toward performance signals β ROAS, CTR, conversion rate β will face some pull toward what's statistically working. That's not unique to ad-vertly; it's the core tension in performance marketing. What we try to do differently is keep the creative loop within your brand context and your session history rather than pulling from cross-account averages. But I won't pretend that's fully solved at scale β it's something we're actively thinking about.
One thing worth noting: our Creative Reasoning Benchmark (ACRB) scored ad-vertly at 19.73/20 specifically on contextual understanding and actionable improvements β tested across 108 real-world ads across 6 verticals and 3 geographies. The biggest edge over generic LLMs was in contextual understanding: recognizing that what works in D2C fintech in the US is not the same as what converts for a local food brand in Asia. That specificity is the architecture we're betting on as the guard against flattening. The marketers who'll get the most from ad-vertly aren't the ones offloading creative judgment β they're the ones who have a strong strategic point of view and want the execution friction removed. The distinctiveness still has to come from somewhere, and that somewhere is the human on the other end of the conversation.