I was losing customers and didn't even know it.

Someone on Reddit was asking about tools like mine. Perfect opportunity, right? Except I found out three days later. Three days. By then, the thread was dead and someone else had swooped in.

This happened again. And again.

So I tried the "proper" social listening tools. You know the ones. Enterprise. Dashboard with seventeen tabs. Setup wizard that takes forty-five minutes. Monthly cost that makes you wince.

They're built for brands monitoring Super Bowl campaigns, not for someone running a small SaaS with their laptop and a dream.

Here's What's Wrong With Social Listening

The big players assume you've got a team. A budget. Time to configure Boolean queries and train junior staff on their Byzantine interface.

They're optimised for quarterly reports, not for "someone just mentioned my competitor and I need to reply in the next hour."

And the pricing? Insane. You're paying for features you'll never use, data you don't need, and support for platforms that don't matter to you.

What We Actually Need

I just wanted to know when people talk about my space. That's it.

I wanted alerts I could actually act on. Not a firehose of noise. Not sentiment charts I'd ignore. Just the good stuff, filtered intelligently, delivered when it matters.

I wanted to reply quickly. Helpfully. While the conversation's still warm.

So We Built Overheard

It monitors keywords across Reddit, Twitter, and other places your customers actually hang out. AI figures out what's worth your attention and what's just noise. You get alerts. You reply (we'll even suggest responses). Done.

No setup wizards. No enterprise onboarding calls. No paying for a marketing team's worth of seats.

Here's the controversial bit: most "social listening" is just corporate vanity. Brands obsessing over mentions they can't do anything about. We built Overheard for people who actually want to have conversations, win customers, and help people.

It's social listening for builders, not boardrooms.

That's it. That's why Overheard exists.

We're opening up access soon. Join the waitlist if you're tired of missing conversations that matter.

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Here's the thing about AI tools: they're all good at different things.

Claude's brilliant for code reviews. ChatGPT crushes research. Gemini's fast for quick questions. Grok brings the spice.

But using them meant living in browser tab hell. Copy, paste, switch, repeat. Ask the same question four times. Compare answers. Waste time.

It felt stupid.

The Aha Moment

I was debugging a gnarly function at 2am. Asked Claude. Got a solid answer. But something felt incomplete.

So I asked ChatGPT the same thing. Different perspective. Better solution.

Then it hit me: Why am I doing this manually?

What if I could just type one message and get six AI perspectives at once? Let them duke it out. Cross-validate. Challenge each other's assumptions.

That's when I started building Nattr.

Everyone's Building the Wrong Thing

The AI tool space is obsessed with wrappers. Pretty UIs around a single model. Pick your favourite, lock yourself in.

That's backwards.

The future isn't "Which AI is best?" It's "Why choose?"

Every model has blind spots. Every provider has strengths. Using just one is like hiring a consultant and refusing to get a second opinion.

One Week, Six AIs, Zero BS

We built Nattr in one weeks of intense work. No funding rounds. No pitch decks. Just us and Claude Code, building the tool we wanted to exist.

Six AI providers in one chat. Type @all and they all respond. Toggle web search on. Watch them collaborate in real-time.

Claude can be your code reviewer. ChatGPT your research assistant. Gemini your quick-answer machine. All in the same conversation.

Want the same model playing different roles? Add three Claudes with different personas. One debugs, one reviews code quality, one challenges your architecture choices.

What We Actually Built

Nattr isn't trying to be everything. It's doing one thing well: letting you use multiple AIs without the copy-paste hell.

No revolutionary AI breakthrough. No proprietary model. Just a better way to work with the tools that already exist.

Sometimes the most useful product isn't the most innovative one. It's the one that removes friction from your actual workflow.

That's Nattr. Six AIs, one conversation, zero tab-switching.

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Why We Built Domain Checker

 Last month I was helping our outbound team set up new sending domains. We needed 20 available
 domains with variations of our brand name. You know, like getprecode.com, useprecode.co,
 precodehq.io - the usual cold email infrastructure.

 Simple task, right?

 I spent three hours checking domains one by one. Copy domain name. Paste into registrar. Wait for
 the "sorry, taken" message. Repeat.

 That's not work. That's punishment.

 So I did what any reasonable person would do: I built a tool to fix it.

 Domain Checker does one thing well. You type your brand name. You pick which TLDs you care about.
 You tell it how many available domains you need. It finds them.

 That's it.

 No account creation. No API keys to manage. No 47-tab pricing comparison. Just type, click, get
 results.

 The tool keeps checking variations until it finds what you asked for. Need 20 available domains?
 It'll check 50, 100, 200 if that's what it takes. You see results as they come in - no waiting for
  some loading spinner to finish.

 When it's done, export to CSV or copy straight to clipboard.

 We could have added a million features. Saved searches. Purchase integration. Price comparison.
 User accounts. All the stuff that turns simple tools into bloated software.

 We didn't.

 Not because we couldn't. Because the point was to solve that specific problem - finding available
 domain variations without wasting your afternoon.

 Cold email teams shouldn't spend their time hunting for domains. They should spend it writing
 emails that help people.

 We built Domain Checker so you can get back to the work that matters.

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