Skip to main content

We use cookies for analytics. Privacy

Back to Work
Sales & Marketing/ Case study

Overwatch

SEO and AI-search intelligence, with every change behind a human approval

Built with

TypeScript / React / PostgreSQL

Inside the project

01 / 03

The decision queue pairs each proposal with its exact change and a clear review action.

Application views show actual Overwatch components in an isolated UI demonstration with fictional data and execution disabled. Captured September 5, 2026.

Overwatch1 / 3

Overwatch approval queue with fictional proposed SEO changes

The decision queue pairs each proposal with its exact change and a clear review action.

The brief

The problem

Buyers now find a business through AI answers, map packs and classic rankings, and each of those is measured in a different rented tool. The data sits in someone else's dashboard, the history leaves when the subscription does, and none of it connects to the work that would improve the site.

Our approach

We built our own platform and host it ourselves. It gathers search, analytics, local and page-experience signals for each site, and it tracks whether AI assistants mention and cite the business. An operator agent reads that data and proposes specific changes. Every proposal waits in a review queue that shows the exact change, so a person decides what ships.

Features

What it does

  1. 01

    See search from more than one angle

    Traditional rankings, AI visibility and local search views answer different questions. Overwatch brings those perspectives into one place so operators can investigate how a site is being discovered.

  2. 02

    Connect visibility to site health

    Core Web Vitals, search data and technical monitoring sit alongside the visibility reports. The workflow connects an observation in search to the website work that may need attention.

  3. 03

    Run the checks repeatedly

    Background workers gather and refresh the data behind the reports. The self-hosted application supports ongoing operations across multiple sites rather than a single exported audit.

Results

What happened

  • In production and in daily use

  • Classic rankings, AI-search visibility and local presence in one view

  • Visibility connected to site health, so a drop points to the page that needs work

  • Agent-proposed changes held in a review queue until a person approves them

  • Data and history kept on our own servers

State
In production
Covers
Search, AI answers, local
Changes
Human-approved
Hosting
Self-hosted

Working on something similar?

Tell us what you are building or fixing.