AI SEO Agent

Find SEO opportunities worth acting on.

Kanso brings together your site's technical analysis, Search Console data and Lighthouse results, turns them into recommendations that show their evidence, and follows each one through action and verification.

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Recommendation
Metadata review/pricingActive
Add a meta description to the pricing page

The pricing page has no meta description. Write a short summary of the page that search results can show, and add it to the page's HTML.

AI-generated suggestion
Why

The public analysis found no meta description on this page.

Evidence Kanso saw
Public analysisNo meta description found on /pricing
Search ConsoleThe page appears in search results in the selected period
What the data cannot establish
Search Console reports a limited window and can lag behind the live site
Potential action: SEO metadata editSupported by the evidence
Illustrative example. The company, pages and repository shown are invented, not real data.
The problem

SEO work stalls between the report and the fix

Finding issues is the easy part. Understanding them, deciding what to do and knowing it worked is where the time goes.

Data lives in separate tools

Search performance, crawl reports and speed tests sit in different places, each with its own view of the same site.

Technical issues take investigation

A report says something is wrong. Working out which page, why and what to change is the real job.

Everything looks urgent

Without context about your site, it is hard to tell which findings deserve your limited time.

Generic advice

Recommendations that ignore your pages, your data and your product read like a checklist.

Reports stop at the report

A list of issues is not a plan. It has no owner, no next step and no way to follow the work.

Nobody checks the fix

Once work is marked done, it is rarely confirmed on the live page.

The difference

Without Kanso, and with it

Without Kanso
  • Collecting reports from several tools
  • Investigating each issue by hand
  • Deciding what matters on instinct
  • Turning findings into tasks yourself
  • Tracking the work in a separate system
  • Checking the live page later, if at all
With Kanso
  • Evidence gathered from your site, Search Console, Analytics and Lighthouse
  • Findings turned into structured recommendations with reasoning
  • You review each one before anything happens
  • Approved work becomes a tracked task, or a reviewed pull request for supported fixes
  • A re-check of the live page to see whether the fix is there
What it is

Evidence, recommendation, action, verification

The SEO Agent is built around a chain, not a report. Each recommendation points at the evidence it came from, each action stays attached to its recommendation, and each fix can be checked against the live page.

01

Evidence

Facts observed on your site and in your Google data.

02

Recommendation

A reasoned suggestion that points back to that evidence.

03

Action

A tracked task, or a pull request you review.

04

Verification

A fresh look at the live page against a stated condition.

It recommends. You decide.

Kanso does not edit your website by itself, and it does not promise rankings or traffic. It tells you what it saw, why it matters and what could change, and the work happens when you or your team do it, or when you approve a pull request.

How it works

From evidence to a verified fix in four steps

STEP 01

Inspect

Kanso collects what it can observe about your site before it recommends anything.

  • Analyzes a sample of up to 25 public pages, plus your robots.txt, sitemaps and links
  • Connects to Search Console and Google Analytics with read-only access
  • Runs Lighthouse through Google's PageSpeed Insights when you ask
  • Refreshes Search Console data daily and the public analysis weekly
SEO Agent
Evidence sources
Public analysisLatest run complete
Search ConsoleConnected
Google AnalyticsConnected
PageSpeed auditRun on demand
Observed on the site
/pricingNo meta description
/aboutA link on this page returns an error
/No structured data
Illustrative example. The company, pages and repository shown are invented, not real data.
STEP 02

Prioritize

Evidence becomes recommendations you can read, question and dismiss.

  • The AI reads only the facts Kanso assembled, in one explicit run at a time
  • Each recommendation names its page, category and reasoning
  • Observed data is shown separately from what the data cannot establish
  • Wording is labelled as an AI-generated suggestion, never as fact
Recommendation
Metadata review/pricingActive
Add a meta description to the pricing page

The pricing page has no meta description. Write a short summary of the page that search results can show, and add it to the page's HTML.

AI-generated suggestion
Why

The public analysis found no meta description on this page.

Evidence Kanso saw
Public analysisNo meta description found on /pricing
Search ConsoleThe page appears in search results in the selected period
What the data cannot establish
Search Console reports a limited window and can lag behind the live site
Potential action: SEO metadata editSupported by the evidence
Illustrative example. The company, pages and repository shown are invented, not real data.
STEP 03

Act

Approved recommendations turn into work that is tracked.

  • An action task moves from open to in progress to marked complete by a person
  • Where an action calls for it, the owner approves before work starts
  • For supported metadata fixes, preview the exact change and have Kanso open a pull request
  • Kanso never merges or deploys. You do
Action tasks
Review page metadataNo approval needed

Review the page metadata flagged for /pricing and correct it in the system that produces this page's HTML.

  1. Open
  2. In progress
  3. Marked complete by a person
What Kanso does not know

Kanso does not know which file or template produces this page.

Potential code change
Repository acme/website
Meta descriptionAI proposal
Plans and pricing for Acme, with a free tier to start.

Kanso opens the pull request. It never merges or deploys.

Illustrative example. The company, pages and repository shown are invented, not real data.
STEP 04

Verify

Finished work is checked against the live page, not assumed.

  • Kanso looks at the public page again and tests a stated condition
  • Conditions include a title, meta description, canonical link, main heading, structured data, viewport tag, HTTPS and a healthy response
  • The result is verified, unchanged or inconclusive
  • Tasks without a checkable condition are never called verified
Verification
Meta descriptionVerified
Expected

A meta description exists and has text

Before
No meta description (observed in the public analysis)
After, on the live page
A meta description is present on the live page
Verified: the expected condition was observed

Verified means this condition was observed on the page. It does not mean rankings or traffic changed.

Illustrative example. The company, pages and repository shown are invented, not real data.
In the workspace

Recommendations you can work through

Active recommendations sit in one list, each with its page and category. Open one to see its evidence, its potential action and what happened next.

SEO & GEO recommendations
ActiveSupersededDismissed
Add a meta description to the pricing page
/pricingMetadata reviewActive
Fix a broken link on the about page
/aboutInternal link reviewActive
Add structured data to the homepage
/Structured data reviewActive
Illustrative example. The company, pages and repository shown are invented, not real data.
Capabilities

What the SEO Agent does

Public site analysis

Samples up to 25 pages for titles, descriptions, canonicals, headings, structured data, image alt text and social tags.

robots.txt and sitemap checks

Reads your robots.txt and sitemaps and flags missing files, blocked pages and sitemaps not declared in robots.txt.

Link analysis

Checks internal and external links for errors, redirects and long chains, and reports the ones it could not check instead of calling them fine.

Search Console insights

Brings in queries, pages, devices and search appearance for the property you choose, refreshed daily.

Analytics context

Adds Google Analytics landing-page and organic data, so recommendations can reflect how pages are actually used.

Lighthouse and Core Web Vitals

Runs Google's PageSpeed Insights on demand and shows Lighthouse results for mobile and desktop.

Evidence-backed recommendations

Each one names its page, its reasoning, the observed data and what that data cannot establish.

Action tasks and pull requests

Track the work as a task with an audit trail, or preview and open a pull request for supported metadata fixes.

Verification

Re-checks the live public page against a stated condition and reports verified, unchanged or inconclusive.

Built differently

SEO shouldn't stop at a report

Most tools end when the findings are listed. Kanso carries each one forward until it knows whether the fix is in place.

01
Discover
Evidence gathered
02
Explain
Reasoning shown
03
Recommend
Structured suggestion
04
Act
Task or pull request
05
Verify
Live page re-checked

Every recommendation shows its evidence

The facts behind a recommendation are resolved by Kanso from its own data, not written by the model, and each is marked as observed, derived or a limitation.

Changes stay under review

Tasks record who did what. Pull requests change one file with a small, previewed edit, and Kanso does not merge or deploy them.

Fixes are checked, not assumed

A task marked complete is only a person's word. Verification looks at the live page and says plainly what it did and did not observe.

Why automate

Why automate the legwork of SEO

The judgment stays with you. What can be repeated reliably does not need to be done by hand.

Checks run the same way every time

A crawl and its findings do not depend on who looked or how much time they had.

Evidence stays current

Search Console data is refreshed daily and the public analysis weekly, without a manual export.

Recommendations know your site

They are written against your own pages, your data and your company documents.

Nothing falls through

Each recommendation can become a tracked task, and finished work can be checked.

Compared

Kanso SEO Agent, a manual workflow, or a generic AI assistant

Manual SEO workflowGeneric AI assistantKanso SEO Agent
Project-specific evidenceYou gather it from several toolsOnly what you paste into the promptYour public site, Search Console and Analytics, assembled for you
Search Console contextExported and read by handNot connected unless you paste dataConnected with read-only access
Technical analysisSeparate crawler and manual reviewCannot inspect your site on its ownBuilt-in public analysis of up to 25 pages, plus on-demand Lighthouse
Structured recommendationsWritten up by whoever does the auditFree-form textTyped by category, with evidence and stated limits
Action workflowA separate task trackerNoneTracked tasks, or a reviewed pull request for supported fixes
VerificationRe-audit laterNoneRe-checks the live page against a stated condition
Recurring executionWhenever someone has timeOnly when you askDaily data refresh and weekly public analysis

Tools and workflows vary. This describes the typical case of working by hand, or with a general AI assistant that is not connected to your data.

Part of Kanso, not a separate tool

The SEO Agent works from the same company documents as Kanso's other agents. Start with your website, and see the pricing page for which plans include it.

See pricing →

Got questions?

SEO Agent questions

Use cases

Where the SEO Agent is used

These use cases name this agent in their workflow. Each one says what it produces and where you stay in control.

Browse all use cases

Turn your site's evidence into work that gets done.

Kanso finds what is worth fixing, helps you act on it and checks the result. Enter your website to start.

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