We turned PostPost.ai on. You paste your website address, and a few minutes later you are looking at a content plan for the week and a set of posts, carousels and stories that actually look like your brand, ready to approve and schedule.
That is the product. The rest of this post is why it exists, because the honest version is that we built it for ourselves before we built it for anybody else.
The day a week we were quietly losing
Our team spent years on Turbologo, a logo and brand identity maker that millions of small businesses have used to get their first real look. Turbologo is a normal company with normal social accounts: Instagram, Facebook, LinkedIn, X, Threads, Telegram.
And every week, the same ritual. Somebody decides what we are posting about. Somebody writes the captions. Somebody opens a design tool and makes the visuals. Somebody resizes them per network, because a square that works on Instagram is wrong on X. Somebody loads it all into a scheduler. Split across a few people it never felt like a big number, so nobody ever flagged it. Added up, it was most of a working day. Every week. Forever. For work that leaves nothing behind: no product, no feature, no asset, just this week’s posts.
What bothered me was not even the hours. It was that the output stayed inconsistent anyway. Some weeks were good. Some weeks we posted twice and called it a strategy.
ChatGPT did the easy 20 percent
I tried to fix it the way everybody tries to fix it. I opened ChatGPT.
It writes a decent post. Then you notice it does not know your prices, your services, your tone of voice, or the fact that you never use exclamation marks. So you rewrite half of it. Then you need an image, so you generate one, and it comes back in colors that are not your colors. So you open a design tool and rebuild it. Then you download it, open the scheduler, upload, retype the caption in their editor, pick a time, and start over for the next network. Do that six more times and you have a week.
The generator did the fun 20 percent. I was still doing the boring 80: the shuttling, the brand fixing, the resizing, the scheduling. And every session started from zero, because the model remembered nothing about my business from the last one.
That was the moment the product got obvious. The missing piece was never generation quality. It was memory and context.
And it was not just us
Turbologo gave us an uncomfortably clear view of the same problem at scale. People come to us to solve identity: a logo, colors, fonts, a look they are proud of. We hand it over, they launch, and then the actual job starts. Show up every day, on five channels, forever, looking like the same company each time.
Very few small businesses win that game. Not because they are lazy, and not because they are short of things to say about their own business. They are short of the four hours a week it costs to turn things worth saying into finished, on-brand, correctly sized posts.
That is a problem worth building for, and it sits directly next to work we had already been doing for years.
Why we thought we could build it
We had been shipping AI generators in production for a long time at Turbologo: logos, icons, illustrations, whole websites. That work teaches you something specific and not very glamorous.
Getting a model to produce something is easy. Getting it to produce something that looks like one particular brand, again and again, at a quality you would actually publish, is the hard part. And it is mostly not a prompt problem. It is a context problem.
So we built the context layer first.
PostPost reads your website and builds a brand profile out of it: your logo, your colors, your fonts, what you sell and at what price, who you are talking to and how you sound.
We call it the brand vault, and it is the reason the output looks like you instead of looking like AI. Every post is generated against that profile rather than against a blank prompt.
What we launched
Add a brand by pasting a URL. Then read back what we understood about the business and correct anything we got wrong. That takes a couple of minutes and it is the only setup there is.
Get a plan for the week, not a pile of posts. Educational and selling posts mixed on purpose, spread across your channels, written per network. X and Threads get shorter, native posts. Instagram gets carousels and stories.
Approve, edit, or just write to it like a message. “We are running a 20 percent sale on Friday, here are two photos” is a valid brief. It comes back as finished posts.
Publish to eight networks: Instagram, Facebook, Threads, X, TikTok, YouTube, Telegram and LinkedIn. Comments and direct messages arrive in one inbox instead of six apps. Analytics show what actually worked, and posting times already learn from your own numbers. Feeding topic performance back into next week’s plan is the next thing we are building.
Work as a team. Roles and approvals for teams, and for agencies, many brands in one workspace, each with its own vault, palette and channels.
What it is not
It is not an autopilot, and I do not want to sell it as one.
No AI knows that you shipped something on Tuesday, that a customer sent you a great photo, or that you decided to push the workshop instead of the course this month. That signal is yours, and it is the part that makes content worth reading. The product’s job is to take that signal and turn it into a week of finished, on-brand content in minutes, not to pretend it can run your marketing without you.
That distinction is deliberate. It is the difference between a co-pilot and a content firehose, and everybody can tell which one they are reading.
Where we are now
The first version went from empty repository to live product in three months and about 2,400 commits. Plans start at $59 a month, and you can see what it makes for your own business before you decide anything: paste your website on the home page and watch what comes back.
If it gets something wrong about your brand, tell us. Right now that is the most useful thing you can send us, because it goes straight into the layer everything else is built on.