Technical SEO · Automation · Native iOS Q3 retainers open

Engineering
compounding growth
for the algorithmic age.

One studio for search, automation, and native iOS — owned by the same brain end-to-end.

PYC is a one-strategist studio for founders who want a system, not a slide deck. We design the SEO infrastructure, build the automation that runs it, and ship the iOS app it points at — so the work compounds instead of fragmenting across three vendors and four invoices.

Start a project → Read the practice ↓

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Exhibit 01 Scale

The number we keep coming back to is eighty per cent.

Across three recent retainers, that is the average reduction in manual SEO operations after we automate the work end-to-end: keyword clustering, content briefs, schema injection, internal linking, performance reporting. The team keeps its judgement and loses its drudgery. The site keeps shipping while everyone is asleep.

3×

faster brief-to-publish cycle

22

named tools, one workflow

Methodology

Pre/post hours logged in Toggl over the first 90 days of each retainer, divided by total task volume. Not a marketing figure.

Stack Twenty-two tools, one workflow.

Make / n8n / Zapier / Airtable / Google NLP / Sitebulb / Ahrefs / SEMrush / SurferSEO / Clearscope / OpenAI / Claude / Pinecone / LangChain / GA4 / PostHog / Stripe / Supabase / Swift / SwiftUI / Firebase / OneSignal

Recent practice The shape of current briefs.

Active engagements are under NDA; the kinds of work are not.

  1. Prestige automotive — multi-year retainer covering technical SEO, content systems and a programmatic landing pipeline for a high-trust workshop brand.
  2. SaaS · QMS compliance — entity-driven content architecture and editorial automation for a regulated category where every page has to defend itself.
  3. Local trades, multi-site — local SEO at scale with schema, GMB automation and a programmatic city-page build.
  4. iOS · indie founder — a SwiftUI app shipped with ASO, Stripe, Supabase and analytics in the same brief.
Exhibit 02 · Search engineering / seo-engineering

SEO is an engineering discipline, not a content opinion.

We treat search like systems work: a graph of pages, entities, signals, and queries, instrumented end-to-end so improvements compound instead of evaporating with the next algorithm note.

Tool stack
  1. Google Search Console for intent and performance signals
  2. Google NLP API for content scoring, sentiment and salience
  3. Sitebulb for deep structural audits and internal linking gaps
  4. Ahrefs and SEMrush for backlink audits and competitor mapping
  5. SurferSEO and Clearscope for semantic content planning
  6. OpenAI and Claude for automated briefs and keyword clusters
  7. Pinecone or Weaviate for vector search and entity gap analysis
Exhibit 03 · Automation / automation

Workflows that keep shipping while everyone is asleep.

A single keyword goes in. A clustered brief, schema block, internal links and an approval-ready draft come out. We design the pipeline, document the failure modes, then hand the team the keys.

  1. Make, n8n and Zapier as the orchestration layer
  2. Airtable and Google Sheets as the operations surface
  3. Webhooks, APIs and JSON for the data plumbing
  4. LangChain, Claude and OpenAI for the enrichment steps
Recent automations
  1. Keyword → cluster → brief → schema → internal links → publish-ready
  2. Competitor NLP and EEAT scoring, prioritised by gap value
  3. GMB posting from blog metadata, on a daily cadence
Exhibit 04 · Native iOS / ios-apps

Native iOS, designed for the way people actually find things.

We build Swift and SwiftUI apps the same way we build sites: with search structure, deep linking and ASO baked in from the first commit, not bolted on by a separate vendor in month six.

  1. Swift and SwiftUI as the default stack
  2. Auth with Auth0, Firebase or Supabase
  3. Payments through Stripe
  4. Push via OneSignal or Apple Push directly
  5. Analytics in Fathom, PostHog or Segment
  6. App Store metadata authored alongside the build, not after it
Exhibit 05 · Content systems / content-systems

Content built around the entities Google actually reads.

EEAT alignment, entity coverage and topical authority as a system, not a checklist. The same approach scales from a Shopify catalogue to a SaaS knowledge base to a local services directory.

  1. SaaS knowledge bases and compliance content
  2. Ecommerce on Shopify and marketplace listings
  3. Local services SEO for high-trust trades
  4. Pillar pages and editorial long-form
How we plan
  1. Ahrefs paired with Google NLP to reverse-engineer competitors
  2. Surfer and Clearscope for entity coverage targets
  3. Airtable calendars filtered by volume, intent and freshness
Exhibit 06 · Integrated system / full-system

One workflow that owns search, content, app and report.

Most studios sell you a piece. PYC ships the rest of the stack too, so the briefing system, the build system and the reporting system speak to each other instead of fighting for credit.

  1. Keyword clustering with intent paths
  2. Internal linking as a continuous job, not a quarterly project
  3. Schema injection and structured-data hygiene
  4. App Store content and search metadata in the same pipeline
  5. Dashboards with GSC, GA4 and Fathom side by side
  6. AI briefs, GMB posts and reports on the same cadence
Exhibit 07 · Disposition / why-pyc

What changes when you commission PYC.

You stop paying three vendors to argue with each other. You start paying one operator to make decisions on a Friday and ship them by Monday.

  1. One full-stack strategist, fluent in frontend, backend and search
  2. Automation-native by default — manual hours fall by about 80%
  3. Entity-first thinking, built for the way Google now parses pages
  4. Platform-aware — CMS, apps and marketplaces, not just one of them
  5. Agile enough to execute on Monday, strategic enough to compound by Q4