I built a disappointment-as-a-service app for your bad brand names.
Hey everyone,
About three months back, I started working on a markdown service(yes i know it was kinda stupid anyways to make a markdown service when therees 10000+ that already exist and do the same thing ) called "JustPaste." I snagged a .co domain since the .com was already taken, thinking I was all set.
Then I did a quick Google search. To my surprise, 'justpaste' is a huge, well-established site. My "available" domain turned out to be completely off-limits. I had to ditch the name and start fresh.
The next week was a blur of GoDaddy in one tab and Google in another, bouncing between name ideas, checking domain availability, and hunting for competitors. It felt like a frustrating, endless cycle. I knew there had to be a smarter way to do this.
That’s when I decided to create CenterPage. It’s the tool I wish I had from the start. It brings everything together on one platform and uses AI to give you a single viability score (ranging from 0 to 100) for your brand name in about a minute. It doesn’t just check if a domain is free; it tells you if the name is genuinely usable.
But what if you have competitors?
To tackle that I included a Deep Scan feature. well what is a "Deep-Scan" you might ask ,well in simple terms It leverages Puppeteer(was gonna go with playwright but went with puppetter instead) and AI to analyze competitor websites.
Think of the AI as a team of consultants, providing you with a strategic breakdown of their:
Technical foundation
Content & SEO strategy
Visual & UX design
It even identifies their tech stack with around 95% accuracy. It’s impressively effective. Plus, you can download the complete report as a PDF.
Here’s a quick GIF showing the main analysis in action:
So, why isn’t it free?
Well, the APIs (GoDaddy, Google, OpenAI) and backend hosting come with real costs. I’m a solo founder without any VC backing just a brokie trying to tackle a problem.
That’s also why I opted for a pay-per-use credit system instead of a subscription model. Founders don’t launch a new brand every Tuesday. You’ll get a few free searches to kick things off, and if you need more, you can grab a one-time credit pack. No ongoing fees.
The site is live now, and I would really appreciate some honest feedback from this community. Does this address a problem you’ve encountered?
ps- there might be some bugs i fixed as much as i could but please if you encounter any serious bugs please do let me know ill really appreciate it.
This is fantastic. The pain of bouncing between GoDaddy, Google, and a dozen other tabs is so real. You've taken a chaotic, emotional process and turned it into a clear, data-driven score, that alone is a huge win.
The Deep Scan feature is the real killer app here. I'm curious, how does the AI differentiate between a "good" and "bad" content strategy when analyzing competitors? Is it looking for keyword density, content structure, or something else?
Seriously impressive work, and the pay-per-use model is a massive plus. Congrats on the launch!
Hi CreatorStackAI ,
Thank you for commenting ,this is indeed a huge paint point im glad it resonates with you and to answer your question about the deep scan
so from a high level, the "AI Content Marketing Strategist" agent is prompted to perform a qualitative analysis much like a real consultant would which is the aim . It's looking for things like:
Value Proposition & Clarity: Does the landing page immediately answer "What is this?" and "Who is this for?"
Target Audience Evidence: Does the language and tone speak to a specific customer profile?
Call to Action (CTA) Effectiveness: Are the CTAs clear, compelling, and strategically placed?
Trust & Social Proof: Is there evidence of customer testimonials, case studies, or logos?
to clarify even more ,lets dive a bit on how the code handles this when a scan is initiated, the backend doesn't just make one big call to the OpenAI API. Instead, it uses 'Promise.all ' too run multiple, independent AI analyses concurrently
Concurrent Analysis: I have several specialized AI "agents" (like the 'Technical SEO Analyst', 'UI/UX Design Consultant', and the 'Content Marketing Strategist' you asked about). Each one receives the same scraped website data from Puppeteer but is given a completely different system prompt and instruction set. They all run at the same time, which is much more efficient.
The "Chief Strategist" AI: This is the final and most important step. Once all the specialist agents have returned their individual analyses, their outputs are collected. Then, a final, higher-level "Chief Marketing Strategist" AI is invoked.
Putting it all together : This is a chief AI (think of him as a mean looking serious workaholic who loves perfection) its only job is to read the reports from all the other agents and synthesize them into a single, cohesive, and actionable "Strategic Battle Plan." It looks for patterns, resolves conflicting points, and prioritizes the most important insights for the user.
So, it's a multi agent system where a final synthesis step turns parallel streams of specialized data into a unified, easy-to-read report. It was a lot of fun to build out that logic,this feature alone took me almost 3 months it was quite a challenge
This is sick — genuinely love the “AI consultant” angle with the Deep Scan. It’s not just a clever feature, it actually speaks to a real founder pain — you think you’ve got a great name, then Google humbles you. 😅
Also respect the pay-per-use model. Feels founder-first and avoids locking people into subs they don’t need. I could easily see this becoming a go-to link people pass around in group chats when someone says “I’ve got a name idea.”
Excited to try it out — rooting for you!
Hi gwarfield,thank you so much for commenting and giving feedback.I really appreciate it
You bet!