Mygom.tech

We ran an SEO audit on our own site last month.

93/100 health score. Solid, right?

Then we dug deeper.

One keyword dropped 25 positions in a single week. Not because the content was bad - the content scored 100/100. Because 2MB of inline JavaScript was killing our Core Web Vitals. Google demoted the page silently. No warning. No explanation.

We only caught it because correlated the keyword drop with the technical scan and flagged the exact file causing the problem.

Old workflow: keyword drops → open Ahrefs → open GSC → open PageSpeed Insights → open Screaming Frog → spend 3 hours guessing.

New workflow: keyword drops → MygomSEO shows the root cause → fix it.

This is what an SEO audit looks like when all your data is connected.

Not a list of 200 issues ranked by "importance."

A diagnosis. With a fix. In one place.

Most marketing teams run 4-5 tools just to stay visible online.

One for SEO audits. One for keyword tracking. One for writing blog posts. One for scheduling social content. One for checking if any of it actually worked.

That's €400–800/month in subscriptions. Plus the switching cost. Plus the context loss between tools. Plus the agency you hired to make sense of it all.

There's a simpler way to think about this.

What if your SEO agent knew your brand voice, tracked your rankings, wrote your content, and posted to LinkedIn - all from one conversation?

That's what we built. It's called .

Not another dashboard. An AI that does the work.

AI-assisted proposals are everywhere in 2026. But there's a difference between a tool that generates text and one that actually knows your pricing, your tone, and your clients.

Most teams using ChatGPT for proposals hit the same wall. The output is clean. But it's generic. It doesn't know your pricing. It doesn't know your format. It doesn't know what you charged a similar client 6 months ago.

So you spend more time fixing the AI's output than writing it yourself. You didn't save time. You just moved where you lose it.

Real proposal automation needs context. Not just a prompt.

Here's what we built instead:

Role rates hardcoded into the system (FullStack Dev, PM, QA, UI/UX Designer). Every proposal pulls live pricing. No spreadsheet hunting. No manual math.

Reference files from real proposals we've already won. The AI learned our structure, tone, and level of detail from documents that actually closed clients.

Clarifying questions before it writes anything. Scope, integrations, and hosting requirements. Quick-reply options. Seconds to answer.

Section-by-section generation. Not a wall of text. A structured document.

The result: proposals that look and sound like our team wrote them. Because in a way - we did.

This is the gap between a generic AI tool and a custom one.

Context is everything.

Want to see exactly how we built it? Full article in the comments.