Nothing goes unchecked
Every page audited on a schedule, not just the twenty someone remembered.
Freelance AI SEO Automation Expert in Bangalore
Automate the tedious parts of SEO. The rankings are still not for sale.
Most SEO work is repetitive: checking the same things across hundreds of pages, writing metadata to length, generating schema, finding internal links nobody has time to add. That part automates well. What does not automate is judgement, and no tool and no person can promise you a position.
- Repetitive checks automated across every page
- Changes reviewed before they ship
- No ranking promises, ever
- Replies within one working day
Overview
What automation can and cannot do here.
SEO divides into work that is mechanical and work that is editorial. Mechanical: is there a title, is it the right length, does the schema match the page, is this image missing alt text, which pages have no internal links pointing at them, which have been slowly losing traffic for six months. Checking those across a large site by hand is the reason they go unchecked.
That whole category automates, and should. A crawl plus a model that can read a page and compare it against what the page is supposed to be doing produces a far better prioritised list than a generic audit tool, because it can judge relevance rather than only presence. A title tag can exist, be the right length, and still be about the wrong thing.
The editorial half does not automate. Deciding what a page should be about, whether the content is genuinely better than what already ranks, whether a topic is worth covering at all – those are judgement calls, and handing them to a model produces a site that is technically immaculate and says nothing anyone needed.
And the part worth repeating: nobody can promise a ranking. Not me, not an agency, not a tool with AI in its name. What can be promised is that the mechanical work gets done consistently instead of occasionally, which is a real advantage over sites where it does not.
What I offer
SEO automationwork
01
Automated site audits
A scheduled crawl checking titles, descriptions, headings, schema, alt text, canonicals and internal links across every page.
Problems found when they appear, not at the next quarterly review.
02
Metadata at scale
Titles and descriptions drafted to length for hundreds of pages, from what each page actually says.
The 400-page backlog stops being permanent.
03
Schema generation
Structured data built from real page data and validated, rather than hand-written once and left to rot.
Markup that matches the page, and keeps matching.
04
Internal link discovery
Finding genuinely relevant linking opportunities across the archive and proposing them for review.
Orphaned pages get found and connected.
05
Content decay detection
Watching for pages losing traffic and flagging them for refresh with the reason.
Decline caught while it is still cheap to fix.
06
Reporting that explains itself
Monthly reports that say what changed, what it affected, and what is worth doing next.
Something you can act on rather than file.
Key benefits
What changes when the mechanical work is automated.
Six things, none of them a ranking promise.
Metadata actually gets written
Drafted to length for the whole site, then reviewed rather than invented from nothing.
Schema stays true
Generated from the page and validated, so it does not drift from what the page says.
Internal links get added
The highest-value, most-skipped task, proposed for you to approve.
Decay is caught early
Pages losing ground flagged while the fix is still small.
Consistency over intensity
The compounding advantage is doing this every month, which is exactly what automation is for.
Who this is for
Who this suits.
Mostly a question of how many pages you have.
Large content sites
Hundreds or thousands of pages where manual auditing stopped being possible.
E-commerce catalogues
Where product and category metadata is generated badly or not at all.
Sites with an old archive
Years of posts, most of them decaying unnoticed.
Marketing teams of one
Where SEO is a third of somebody’s job and the first thing dropped.
Agencies
Running the same checks across many client sites every month.
Not for: a ten-page site
At that size, doing it by hand once properly is faster and better than building a pipeline.
Where I work
Doing this for Indian businesses, honestly.
The SEO market here has a credibility problem, and it is worth naming. Guaranteed first-page packages, ranking reports for keywords nobody searches, monthly retainers that produce a PDF and nothing else. Plenty of businesses in Bangalore have paid for a year of that and have the reports to prove it. Adding AI to the brochure has not changed the substance.
What I will not do is sell you that with a better vocabulary. No position guarantees, no promise about AI Overviews or ChatGPT citations, no invented traffic forecasts. The automation does mechanical work consistently and shows you the before and after. That is the offer, and it is a smaller one than most pitches.
What does work locally is unglamorous: a Google Business Profile that is complete and consistent with the site, location pages that are genuinely about locations rather than the same page with a city swapped in, and schema that matches reality. Automation keeps those consistent across a large site; it does not invent demand that is not there.
No ranking guarantees
Not from me, not from any tool. Anyone promising positions is guessing or lying.
Local consistency checked
Name, address and phone compared across site, schema and profile.
Before and after, measured
Search Console data, not a vendor dashboard with its own numbers.
Reports you can act on
What changed, what it affected, what is next.
Serving Chennai, Bangalore, India, Canada, UK, USA, Dubai, Singapore.
Industries
Where this pays off.
Page count is the main predictor.
E-commerce
Typically needs: Thousands of products with templated or missing metadata.
How I help: Per-product titles and descriptions drafted from real attributes, schema validated.
Publishers & blogs
Typically needs: A large archive quietly decaying.
How I help: Decay detection, refresh prioritisation, internal links across the archive.
SaaS
Typically needs: Documentation and marketing pages competing with each other.
How I help: Cannibalisation found, intent clarified per page.
Multi-location businesses
Typically needs: Location pages that are near-duplicates.
How I help: Consistency checks and genuinely differentiated location content flagged.
Marketplaces
Typically needs: Listing pages generated without SEO consideration.
How I help: Templated metadata improved, thin and orphaned pages found.
Agencies
Typically needs: The same monthly checks across many sites.
How I help: One pipeline, per-client reports, consistent standards.
How I work
How an SEO automation project runs.
Six steps, starting with a baseline so improvement can be proved rather than claimed.
Discovery
I crawl the site, read Search Console, and work out which problems are widespread enough to be worth automating rather than fixing once.
Planning
We decide what gets automated and what stays human: which checks run on a schedule, which changes need approval, which are never automatic.
Design
Rules and templates are written: metadata patterns per page type, schema shapes, link relevance thresholds, what counts as decay.
Development
The pipeline is built: crawling, analysis, drafting and reporting, with proposed changes queued for review rather than applied.
Testing & SEO
It runs on a sample first. Proposed changes are checked for accuracy, rules are tuned, and the false-positive rate is measured.
Launch & support
Live on a schedule, with monthly reporting against the baseline and a standing review of what the rules keep getting wrong.
Technology
What it is built with.
Your own data, read through tools you can inspect.
Data sources
Search Console APIYour real impressions, clicks and positions.
Site crawlingEvery page read as a crawler sees it.
AnalyticsBehaviour alongside search performance.
Log filesWhat crawlers actually requested, where available.
The analysis
Language modelsJudging relevance and intent, not only presence.
Rule enginesDeterministic checks where rules are clearer than models.
EmbeddingsFinding related pages for linking and cannibalisation.
ValidationSchema and metadata checked against real specifications.
Where changes land
WordPress REST APIChanges queued as drafts in your own site.
Review queueProposals approved or rejected by a person.
Change logWhat changed, when, and who approved it.
ReportsMonthly, against the original baseline.
Features
What every pipeline includes.
Including the limits.
Scheduled crawlsThe whole site, on a cadence.
Metadata draftingTo length, from what the page says.
Schema generationBuilt from page data and validated.
Internal link proposalsRelevance-scored, never auto-applied.
Decay detectionPages losing ground, with the reason.
Cannibalisation checksPages competing for the same intent.
Change review queueApproval before anything ships.
Baseline reportingMeasured against where you started.
Audit trailEvery automated change recorded.
SEO & performance
What I will and will not claim.
I will claim that the mechanical work gets done consistently, that problems are found quickly, that metadata and schema stay correct across the whole site, and that you will be able to see what changed and what it affected.
I will not claim a position, a traffic figure or a timeline for either. Rankings depend on competitors, on your content’s actual quality, and on algorithm changes nobody outside Google sees coming. Any guarantee in this field is a guess with a confident voice, and you have probably already paid for one.
- Titles and descriptions correct and within length, site-wide
- Schema that matches the visible content and validates
- Headings structured, not styled into place
- Internal links proposed on relevance, reviewed by a person
- Canonicals, redirects and indexation checked every crawl
- Core Web Vitals tracked alongside the content work
- Decay flagged early, with the evidence
- No guaranteed rankings, no invented forecasts
AI search
On AI Overviews and answer engines.
No one can promise your content will be cited by ChatGPT, Gemini, Perplexity or Google’s AI Overviews, and services selling “AI visibility” as a guaranteed outcome are selling something they do not control. What you can control is whether your content is clear, structured, attributable and actually worth quoting – which has been the same advice for a decade under a new name.
- One question answered clearly per page
- Answers stated plainly, near the top
- Structured data consistent with the visible content
- Facts attributable and dated
- Content served in HTML, not assembled by script
- No claim made about inclusion in any AI product
Why me
Why bring this to me.
Four things, one of which is a refusal.
I will not guarantee rankings
Not for any amount. Anyone who does is either guessing or counting on you not checking. What I will do is show you the baseline, the changes and the measured effect.
I do the SEO work by hand too
Technical SEO is an existing service here, not a new one with AI attached. I automate the parts I already know are repetitive, because I have done them manually enough times to know which those are.
Nothing ships unreviewed
Proposed changes queue for approval. An automation with write access to a live site and no review step is an incident waiting to be scheduled.
The rules are readable
The thresholds and templates are written down in plain language. If the pipeline is proposing something daft, you can see why and change it.
FAQ
Questions I get asked about SEO automation.
No, and I would not work with anyone who does. Rankings depend on your competitors, your content’s actual quality and algorithm changes nobody outside Google sees coming. I guarantee the work gets done and measured, not the position.
It drafts it, from what each page actually says, to the right length. You review before anything publishes. On a large site that turns an impossible backlog into an afternoon of approvals.
Automating checks, metadata drafting and schema generation is ordinary technical work. What breaches guidelines is generating pages at scale with no value, or manipulating links. The pipeline does the former, and I will not build the latter.
Only with approval. Changes queue for review, and every applied change is logged. Giving an automation unattended write access to a live site is how a bad rule becomes a bad week.
A tool reports; this acts on your own site, in your own rules, and drafts the fixes. A generic audit tells you four hundred pages have short descriptions. This drafts four hundred descriptions for review.
Nobody controls those, and anyone selling guaranteed “AI visibility” is selling something they cannot deliver. Clear, structured, genuinely useful content is what helps, and that is the same advice as before the acronyms changed.
Technical fixes can show within weeks; content and authority work takes months. Anyone quoting you a specific timeline for a specific position is making it up. The baseline means you will at least be able to see what actually happened.
No. At that size, doing it properly by hand once is faster, cheaper and better. I would tell you that rather than sell you a pipeline.
The crawling, analysis and reporting work on anything. Applying changes automatically needs an API, so on other platforms it may produce a reviewed list of changes rather than writing them for you.
You reject it, and we look at why the rule produced it. That is what the review queue and the readable rules are for. The useful question about any automation is not whether it errs, but whether you find out before your customers do.