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Meet Atlas 3
Atlas. PersonaAI inside.

Atlas is your very own marketing assistant

It gives your PersonaAI synthetic customer the tools the create and review campaign content before they go live

Your buyer, in the room when the campaign gets written

Most AI content tools generate plausible-sounding content from training data. Atlas generates from your synthetic customer.
 
The result: content that sounds like your brand, talks to your real buyers, and lands without the approval cycle from hell.
 
Atlas built and in use by life science companies and consultancies of all sizes. PersonaAI inside

 

Three things change with Atlas

GOVERNANCE

Atlas works inside your approved boundaries

Before Atlas creates any campaign content, Strivenn configures the guidance it has to follow. That covers your approved claims, your product terminology, your brand voice, any required language and whatever other campaign rules you set. Atlas works to those boundaries when it drafts and when it reviews. Where your evidence or your approved claims do not support a message, it is built to say so rather than reach for a stronger one.

 

One boundary is enforced by the system itself. Every call-to-action destination Atlas is allowed to use sits on a list you control. The job reads that list live and refuses a destination that is not on it before any work is produced. Retire a destination and it stops being reachable that day.

 

Be precise about the difference when your CEO asks, because the difference matters. The destination list is a gate the work cannot get past. Your claims, terminology and brand voice are configured into the build that does the work, which is a strong constraint and a different kind of one.

 

You set the list, you brief the campaign, you see the work that comes back, and you approve it.

THE AI MARKETING ASSISTANT YOU'VE BEEN WAITING FOR

The buyer shows up whenever they are needed

Atlas does more than ask the buyer a question. It carries that buyer perspective through the whole of campaign development.

 

HOW IT WORKS

Atlas runs on PersonaAI

PersonaAI is the synthetic customer. The buyer evidence base. The grounding layer. Atlas is what publishes from it. Together they do something neither does alone: turn buyer evidence into content that sounds like your brand and respects your approval cycle.

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WHO ATLAS SERVES

One buyer perspective, used across the campaign team

Your voice, in every asset.

"It's like having my very own marketing assistant."

Kristina Whitfield, Marketing Manager, 

Pivotal Scientific

THE LIMIT, AND HOW TO START

Synthetic for directional,

Human for decisional

Most "synthetic customers" are guessing. Someone asks an AI to imagine a buyer, and it invents the answer.

 

The ones Strivenn builds you work from your own research. The interviews you ran. The survey data you collected. The deals you won and lost.

 

Your reviewers will ask about that difference. Have the answer ready.

 

Here is the rule we work to. Atlas writes the work and checks that the outputs match the rules you gave it before you decide what happens next.

 

That is why we start with one campaign. You see how it writes, how it handles your claims, and what comes back, before you commit to anything bigger.

 

Synthetic for directional,
Human for decisional

The Market Research Society has published on where synthetic respondents fail. ESOMAR reached the same conclusion. Read both before you buy anything in this category, including ours.

 

Their criticism is fair, and it lands hardest on the thing most vendors are selling: a model prompted to imagine a buyer, producing answers drawn from an average of the internet and presenting them with the poise of primary research. That critique also applies to us the moment the evidence underneath goes thin, which is precisely why the sealing, the traceability and the refusal behaviour above exist.

 

A Strivenn synthetic customer stands on primary research. Voice of customer interviews. Quantitative survey data. Historical baselines that show how the market moved. Years of observed market signal. That changes what the output is worth. It does not change the rule. Use it to stress-test thinking between research cycles, then validate with real buyers before you commit.

 

The human still owns the decision

A synthetic customer can challenge your assumptions, interrogate the evidence you already own and expose the gaps in your thinking before a launch does it for you. It should not decide whether you launch a product, approve a claim, enter a market or commit investment. Your voice of customer programme, your customer interviews and the people accountable for the final call all stay exactly where they are.

 

Anyone selling you a synthetic customer that closes the loop on its own is selling you something that will fail a professional review, and that review is coming.

Better use of the evidence you already have

 

Your organisation has already bought the interviews, run the surveys and filled the CRM. Most of it is sitting in a folder somebody has to remember to open. A grounded, governed synthetic customer turns that evidence into a buyer your team can question on a Tuesday afternoon, and into an answer you can defend when the questions come from above you.

What you'll walk away FROM THE CALL with:
A diagnosis of where your content is drifting from the buyer
The two highest-leverage points to close the gap
A one-page summary you can defend internally

 

Frequently Asked Questions

Why not just ask ChatGPT to write it?
Do I need PersonaAI before I can use Atlas?
How does Atlas handle claims and approved language?
Will it sound like our brand?
What if we are a small startup with no formal claims docs?
What tools does Atlas connect to?
How fast can we go live?
What training is required?
What proof is there that this works?
Do we get hands-on access to the content tools?
Where does this live, and who has to approve it?
Is our evidence shared with other Strivenn clients?

Championing Responsible AI

As a BSI AI Management Practitioner, Matt is equipped to implement the ISO/IEC 42001:2023 framework, conduct AI System Impact Assessments, and deploy best-practice risk controls, backed by the internationally recognised BSI Mark of Trust.
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