A menu of focused automation services for SEO teams — sitemap generation, URL curation, deduplication, content generation at scale, internal linking engines, and guardrail tooling. Anywhere your team is doing the same thing twice, I'll help you automate it.
At Wayfair I built systems that prevented an estimated $15M in revenue loss through self-service guardrail tooling, cut content duplication by 90% across three languages, and reduced manual SEO intervention by 80%. Before that, at Virtusa, I automated over 200 manual processes across banking development teams.
Every service on this page is something I've built and shipped in production. You'll get working Python code, documented enough that engineering can own it, and a workflow that keeps running after I'm gone.
Below is the full menu. Pick one or several — most engagements combine two or three.
Stop hand-maintaining sitemaps. Get an automated pipeline that generates clean, properly structured XML sitemaps from your live URL inventory — and submits them to Search Console and Bing Webmaster Tools on a schedule.
Python pipeline that pulls your live URL inventory (from your CMS, database, or by crawling), filters out URLs that shouldn't be indexed, and produces clean XML sitemaps split by size and content type — products, categories, articles, etc.
For large sites: a sitemap index file pointing to multiple themed sitemaps (max 50k URLs each, properly split). Critical for crawl budget control and faster indexation tracking.
Automatic submission via the Search Console API and IndexNow protocol whenever sitemaps update. No more manual re-submission, no more stale sitemaps.
For multilingual sites: automated hreflang annotations in the sitemap (more reliable than on-page tags at scale). Tested approach from Wayfair's EN / DE / FR setup.
Most large sites don't have a single source of truth for "what URLs do we actually have?" — and the gap between what's crawlable, what's indexed, what's in the sitemap, and what's published is where ranking problems hide. This service builds that single source of truth.
A unified URL table reconciling sources: your CMS / database, crawl data, Search Console-discovered URLs, sitemap entries, and server logs. With status, last-crawled date, and discovery source for each.
Logic-driven categorisation of every URL: keep & index (greenlight), consolidate to canonical, redirect, or noindex. Driven by traffic, conversion data, content quality, and business rules you define.
Server-log parsing to identify which URLs Googlebot is wasting time on (parameter URLs, faceted navigation, duplicate paths) and recommendations to redirect that crawl budget to the URLs that matter.
A prioritised, engineering-ready list of redirects, canonical changes, and noindex additions — sequenced to minimise traffic risk during rollout.
Cannibalisation kills rankings at scale. This service finds duplicate, near-duplicate, and intent-overlapping content across your entire site — and gives you the playbook to fix it. Same approach that cut duplication by 90% across Wayfair's EN / DE / FR stores.
Python + RegEx pipeline catching pages with identical titles, H1s, meta descriptions, or body content. The low-hanging fruit, automated.
Sentence-transformer embeddings to find pages that aren't textually identical but target the same intent — the actual ranking killer. Catches what RegEx misses.
Cross-referencing Search Console click & impression data to find pages competing against each other for the same queries. Recommends which page to keep, redirect, or re-position.
Specialised pipeline for international sites: identifies duplication that arises from translation drift, regional content overlap, or hreflang misconfigurations.
For sites with repeatable content shapes — city pages, product comparisons, long-tail informational content — an LLM pipeline produces useful pages at a scale manual content can't match. Built and shipped in production at Wayfair since 2022.
Python pipeline that pulls input data (product attributes, location info, query patterns), generates copy via OpenAI or Anthropic APIs with brand-voice prompts, and publishes via your CMS or directly as static pages.
Prompts engineered to match searcher intent at each funnel stage (informational, commercial, transactional) — not generic "write me content about X". The difference between content that ranks and content that doesn't.
Automated checks before publish: duplication scoring against existing content, brand-voice similarity, factual consistency, length and structure validation, plus human-review checkpoint on a sample.
Production-tested workflows for generating in EN / DE / FR / more — with localised prompts (not just translation), local search intent alignment, and hreflang-aware publishing.
Internal linking is the highest-leverage on-site SEO lever most teams under-invest in. This service replaces rule-based or manual internal linking with an ML-driven engine — the same approach that delivered +9% page clicks and +2% SERP position lift at Wayfair.
Sentence-transformer embeddings to identify the most semantically relevant link targets for any given page. Beats keyword-match approaches in both precision and coverage.
Generation of natural, varied, intent-aligned anchor text — avoiding the over-optimised exact-match anchor patterns that trigger Google's penalties.
Graph analysis of your existing internal link structure — identifying orphan pages, link sinks, and opportunities to push PageRank-equivalent equity toward priority content.
Not a one-off script — a maintainable pipeline that re-runs on a schedule, integrates with your CMS, and surfaces changes as engineering tickets or automated PRs.
A self-service tool that prevents non-SEO teams from accidentally breaking high-performing pages. Modelled on the system I shipped at Wayfair that protected an estimated $15M in revenue and reduced manual SEO intervention by 80%.
Automatic flagging of changes to your highest-revenue pages — content rewrites, URL changes, metadata edits, schema removal. Bad changes get blocked or surfaced for SEO review before going live.
Daily checks for changes in indexation status, canonical tag drift, robots.txt rule changes, and accidental noindex tags. Catches the silent killers.
Statistical baselining of organic traffic, impressions, and ranking metrics — with alerting when any deviate beyond expected thresholds. So you find out before your VP does.
A lightweight dashboard or CLI that lets non-SEO teams (merchandising, content, product) check their changes against SEO rules before shipping — removing the bottleneck on the SEO team.
Off-the-shelf crawlers like Screaming Frog cover the basics. For anything site-specific — unusual URL patterns, JS-rendered content, login-walled sections, structured-data extraction — you need custom Python crawlers. This is that.
Custom crawlers tuned to your site patterns — running on a schedule, writing to BigQuery or your warehouse, surfacing the issues that off-the-shelf tools miss.
Headless browser crawling for sites using React, Vue, or other JS frameworks — capturing the rendered HTML Google actually sees, not the empty server response.
Parsing of raw server logs to see exactly what Googlebot, Bingbot, and other crawlers are doing on your site. The most underused SEO signal there is.
Crawlers that pull and validate every JSON-LD, microdata, and RDFa block on your site — checking for schema errors that block rich results.
Audit current SEO workflows and find the recurring tasks. Score them by frequency, effort, and value of the time saved.
Write the spec: inputs, outputs, edge cases, where it runs, who consumes the output, how alerts surface.
Ship Python with tests, deploy to your cloud (GCP / AWS / local), and validate against known cases before going live.
README, runbook, and a walkthrough with engineering. The code is yours — no licensing, no lock-in.