Ask Adora reads every ad the brand ran across its connected accounts. Each one is already labeled with the creative attributes inside it: the scene, the color, the composition, the message, and so on. It ties those attributes to the brand's own ROAS, not an industry average, and finds the pattern. In this case, warm outdoor light and the product in hand outperformed studio shots by a wide margin.

It writes a short brief built on that pattern and grounded in the brand's guidelines. From that, it generates new images from the brand's real products. Finally, it checks every one against the actual product, fixes the label that came out wrong, and puts the set in front of the brand manager to approve.

From that single sentence, the brand manager has received a brief tied to their goals, a batch of on-brand variants, and the evidence for why they should work. Most importantly, they retain control over what goes live or what revisions are made next.

While it felt like interacting with a single tool, multiple agents were working as a team to deliver that brand manager what they needed. What does that agentic teamwork actually look like? Let’s dive in.

How it fits together

You talk to one agent, Ask Adora, and it directs a team of specialists behind the scenes. They all work from the same brand context, and whatever they produce comes back to you for review before anything goes live. Once your ads are in market, their results flow back in to guide the next round of decisions.

Strength in Specialists

Ask Adora is an orchestrator. It is the one agent you talk to, and its job is to understand what you mean, plan the work, hand each piece to the right specialist, check what comes back, and return it to you.

The specialists each do one part of the campaign lifecycle well:

Decide. Analyzes performance down to the creative attribute, spots fatigue, and recommends what to make next.
Create. Writes briefs and concepts from the data, generates and edits on-brand images, resizes to every spec.
Approve. Checks work against the real product, readability, disclaimers and platform safe zones, and fixes what's off.
Launch. Writes copy from a media plan, fills in publishing details from a build sheet, and stages ads for approval.

We built it this way for three reasons.

Focus beats breadth. An agent with one job and the right tools for it makes fewer mistakes than one agent juggling every tool at once.

Each part can be tested on its own. When the QA specialist gets better at spotting a garbled label, we can improve it without re-testing everything else.

The work can grow without a rebuild. A new kind of job means a new specialist under the same orchestrator, not a new product to learn. The way you ask stays the same.

Context is the advantage

Any agent can write a brief. Very few can write your brief. The difference is context, and every agent in Adora works from the same three sources of it.

Your brand. Every brand in Adora starts with its Brand DNA: products, guidelines, creative aesthetic, voice, and the history of what the team has approved and rejected. It sets the bounds every agent works within, so new work looks like it came from the brand, because it did.

Your data. Adora labels every ad with 15 to 20 creative attributes and ties them to the results in the brand's own measurement system. That is why Ask Adora can say which attributes are working for this brand, which are overused, and which haven't been tried yet. Your analytics stay the source of truth.

The context of where you’re working. Ask Adora knows what you're looking at. "These ads" or "the ones I selected" means exactly that. It also fills in the page as it works, so you can keep going in the chat or take the reins and adjust by hand.

This is why a general-purpose agent, however capable, can answer "what do marketers usually do?" but not "what should we make next for this brand?" It doesn't hold the context. Adora does, and it deepens with every approval, edit and result.

The last mile: making it right

Most AI creative stops at "generated." Someone still has to zoom in, notice the emblem is slightly wrong or the label text is garbled, and send it back. That person becomes a retoucher, and the speed AI promised disappears into review.

Adora's QA specialist takes on that step. It compares every generated image to the real product details: shape, labels, logos, emblems. When something is off, it coordinates with the Editor specialist agent to fix just that region and leaves the rest of the composition untouched. It also works from your comments, so "the cap should be matte" becomes an edit, not a ticket.

In approvals, the same specialist checks readability, missing disclaimers and platform safe zones, and leaves its notes as comments for the reviewer.

This is the part that lets a team use AI at volume without worrying about slop. The reviewer's time goes to the judgment calls: is this the right idea, is this the story we want to tell. Not into finding a misspelled label.

A glass box, not a black box

Every brand we talk to is asking the same question about agents: how much control do we hand over? Our answer is built into the architecture.

Agents need two things to do good work: context and direction. Adora supplies the context. The direction is human. You decide where the work points, creatively and strategically, using the taste, intuition and understanding of goals that no system holds for you. The agents do the work. You are the director.

In practice, that means:

You see the work as it happens. Ask Adora shows its steps in the chat. You can direct it throughout. The brief, the drafts and the publishing details land in the pages your team already uses.
Nothing goes live without a person. Every output moves through the brand's existing approval flow. Ask Adora doesn't publish, pause ads or move budget on its own.
Every step is on the record. What the work was made from, which agent made it, who approved it, and how it performed. A brand team, its creative partners and its agency can all see what was made and why.
Each brand's data stays its own. A chat works within one brand. One brand's products, creative and performance are never context for another's.

For an enterprise, this is the difference between allowing AI and adopting it.

How it gets better every day

We built Ask Adora the way we ask customers to run their campaigns: put it in market, read the results, and make the next round from what you learned. Our own team used it on real work first, and we built the system that watches it before we built the fixes.

That system runs on two rhythms.

Every night, an exam. Ask Adora answers a set of real marketing questions with known right answers. If a change makes it worse at something it used to get right, we know before a customer does.

Every morning, a read. The system reviews the previous day's conversations, finds the ones where the agent struggled, and tells us why and what to change. Rather than a dashboard of failure rates, we review an answer with a direction, the same thing we promise customers.

We consider whole conversations, not single messages. What someone wants is spread across a thread: the ask, the follow-up, the correction. If a person had to correct the agent to get there, we count it as a miss, even when it got there in the end.

Fix it once, for everyone

When an agent gets something wrong, the quick fix is to script that one situation. We don't. Almost every miss traces back to something shared: the instructions an agent reads to learn its job, or the way a feature is named and described. Fix it there and every agent, and every future conversation, inherits the fix.

Here's one example. Someone asked Ask Adora to set the primary text on a campaign. The same piece of copy has a different name and a different home on every platform: what Meta calls primary text, Google and Microsoft put in other fields. The fix wasn't a script for that request. We gave the agents a shared map of which copy belongs to which field on which platform, and the rule that an ad is going one place. Now it sets the right field the first time, on every platform, for every brand.

The biggest lesson: the agent almost always understood what someone wanted. The hard part was connecting that intent to the right action, across dozens of tools, fields and settings on every platform. A bigger model doesn’t solve that. Better decisioning does, and that requires clearer, shared descriptions of each tool, like defined roles and responsibilities within a team.

Where it's going

Ask Adora is the first place our customers put this system to work. Underneath it is a network of purpose-built agents for the whole campaign lifecycle, all grounded in the brand's DNA and all learning from the brand's own results.

Over time those agents take on more of the load: more of the briefs, the checks, the trafficking, the weekly performance pull. The part that doesn't move is the person directing it. The marketer closest to the work, with the context and the taste, decides what the brand should say next. The agents make it faster to say it everywhere the brand's customers are.

The best way to understand it is to use it. Ask Adora is available now to every Adora customer. See the prompt guide for where to start.

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