Services
One AI-led team, from audit to production.
Four services that get you agent-ready fast — assess, build, and grow, moving 40–60% faster with Claude and Claude Code.
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Explore the services
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aiFocus
AI readiness
Score your catalog, data, and stack for agent-readiness — and hand you the roadmap.
aiFocus details ↓
aiX
AI creative
On-brand renditions and content at a fraction of agency cost.
aiX details ↓
aiAccelerate
Implementation
Re-platform to machine-readable commerce 40–60% faster, built with Claude.
aiAccelerate details ↓
aiEngage
Marketing AI
Modern demand generation on your HubSpot stack.
aiEngage details ↓Assess → build → grow
One accountable team across the whole arc.
40–60% faster
AI-led delivery with Claude and Claude Code.
On your stack
HubSpot, your platform, your data — no rip-and-replace.
The shift
What agentic commerce actually means
Buying is moving from search-and-scroll to ask-and-agent. When an AI shops on a customer's behalf, discovery, comparison, and checkout collapse into one machine-readable exchange.
For twenty years the website was your best salesperson: it persuaded a human who was doing the comparing. When an agent does the comparing, persuasion gives way to legibility. The assistant checks whether it can parse your products, verify your pricing, confirm your return policy, and trust your availability — and if it can't, you simply aren't in the consideration set. No bounce rate ever tells you it happened.
That is a data problem and an operations problem before it is a technology problem. The merchants winning AI recommendations today aren't the ones with the biggest platforms — they're the ones whose catalog, content, and policies are structured, current, and consistent everywhere a model looks.
The four services map to that arc. aiFocus scores where you stand and hands you the sequenced roadmap. aiX makes creative and content production keep pace with what the plan demands. aiAccelerate rebuilds the commerce layer machine-readable when the platform is the ceiling. And aiEngage turns the demand side into a measurable motion on the HubSpot stack you already own.
One accountable team runs the whole arc, delivering with Claude and Claude Code — which is where the 40–60% compression in time and budget comes from. No handoffs between an audit vendor, a build agency, and a marketing shop; the team that scored the gap is the team that closes it. And everything we build, you keep.
01
Assess
Score your catalog, data, and stack for agent-readiness — and hand you the roadmap.
02
Build
Re-platform to machine-readable commerce, 40–60% faster, built with Claude.
03
Grow
Modern demand generation on your stack, measured by what assistants recommend.
AI readiness
aiFocus
Know exactly where you stand with AI — and what to do first.
aiFocus is a fixed-scope assessment that scores your catalog, data, and platform for agent-readiness, then hands you a prioritized roadmap your team can execute — with us or without us.
Buying is shifting from search-and-scroll to ask-and-agent, and most commerce stacks were never built to be read by a machine. aiFocus answers the question every operator is asking right now: if an AI assistant went shopping on my customer’s behalf today, would it find us, trust us, and recommend us? We audit the three layers that decide that outcome — your catalog (can an agent parse products, pricing, inventory, and policies?), your data (is it structured, current, and consistent across surfaces?), and your stack (can the platform expose what agents need without a rebuild?).
The output is not a slide deck of themes. It is a scored readiness report — where you stand today against the prompts and queries that matter in your category — plus a sequenced roadmap: what to fix first, what it costs, what it returns, and which items are additive versus which genuinely require platform work. Every recommendation is priced against a build estimate, so the roadmap doubles as a budget.
Because the assessment runs on Claude with our GEOPro tooling, it covers ground a manual audit can’t: we test how assistants actually answer category questions today, measure your share of voice against named competitors, and trace which sources the models pull from when they leave you out.
The assessment runs on Claude — the same models your customers ask for recommendations — so the findings reflect how you are actually read, not a theory of it.
Agent-readiness score
A scored audit of catalog, data, and stack — benchmarked against your category, not a generic checklist.
AI share-of-voice baseline
How ChatGPT, Claude, Perplexity, and Gemini answer your category prompts today — and who they cite instead of you.
Sequenced roadmap
Prioritized fixes with effort, cost, and expected impact — additive work separated from platform work.
Executive readout
A working session with your leadership team: findings, the plan, and the first 90 days.
01
Audit
We crawl and score your catalog, data, and stack the way an AI agent reads them.
02
Benchmark
We measure how assistants answer your category prompts and where you appear — or don’t.
03
Roadmap
You get the sequenced, priced plan — and can execute it with any team, including ours.
Engagement shape: Fixed scope, 3–6 weeks. The roadmap is yours to execute with any team — most clients continue into aiAccelerate or GEOPro, but nothing is bundled.
What do we walk away with if we never hire you again?
The complete scored audit, the share-of-voice baseline, and a sequenced roadmap with effort and cost estimates per item. It is written to be executed by any competent team — the roadmap is the product, not a teaser for one.
How is this different from an SEO audit?
An SEO audit scores how search crawlers rank your pages. aiFocus scores how AI assistants parse and cite your business — structured data, machine-readable catalog, policy legibility, and actual assistant answers in your category. Search ranking is one input; being the answer an agent gives is the outcome we measure.
Do you need access to our systems?
Read access helps but is not required to start. The first pass works from your public surfaces — the same view an AI agent has. Platform and analytics access sharpens the cost and effort estimates in the roadmap.
What does it cost?
aiFocus is a fixed-fee engagement scoped in the first call — the price depends on catalog size and how many markets or brands we benchmark. Book 20 minutes with Justin and you will have a number the same day.
AI creative
aiX
Agency-grade creative, produced at AI speed.
aiX is our creative and content production service: on-brand product renditions, campaign assets, and site content generated with Claude and finished by senior designers — at a fraction of traditional agency cost and turnaround.
Creative production has always been the bottleneck between a commerce strategy and a live experience. Every product needs photography or renditions in every context; every campaign needs variants for every channel; every new page needs copy that sounds like you. Traditional agencies solve this with headcount and weeks. aiX solves it with a small senior team running an AI production line: Claude generates, designers direct and finish, and your brand system is enforced at every step.
The word to underline is on-brand. Generic AI output is easy and worthless. aiX starts by encoding your brand — palette, type, voice, product truth — into a production system, so every rendition and every paragraph comes out sounding and looking like it came from your studio. You review at the direction level, not the pixel level.
aiX also feeds the machine-readable layer: the same production pass that creates human-facing content generates the structured descriptions, alt text, and schema that AI assistants read. One pipeline, both audiences.
Production runs on Claude with senior creative direction — the volume of a content farm, the finish of a studio.
Brand production system
Your palette, type, voice, and product truth encoded so AI output is on-brand by default.
Product renditions at scale
Consistent, art-directed product imagery and variants across contexts and channels.
Campaign + site content
Copy and assets for campaigns, landing pages, and catalog — human-finished, machine-readable.
Structured-content layer
Descriptions, alt text, and schema generated in the same pass — content agents can parse and cite.
01
Encode the brand
We turn your brand guidelines and product data into a production system Claude follows.
02
Produce in batches
Renditions and content ship in reviewed batches — you direct, the pipeline executes.
03
Publish everywhere
Assets land in your DAM, storefront, and channels with the structured layer included.
Engagement shape: Runs as a monthly production engagement or a fixed batch (a launch, a catalog refresh, a channel expansion). Typical clients replace 60–80% of a traditional production retainer.
Will the output actually look like our brand?
That is the first deliverable, not a hope. We encode your brand system — palette, type, voice, product truth — before anything is produced, and a senior designer finishes every batch. If it would not pass your creative director, it does not ship.
How much cheaper is this than our agency?
For production work — renditions, variants, catalog copy, campaign adaptation — clients typically see 60–80% cost reduction against agency rates, with turnaround in days instead of weeks. Strategy and original campaign concepts remain human work; aiX makes their execution cheap.
Who owns the assets and the production system?
You do, outright. The brand system, the prompts, the assets, and the structured content are deliverables — if we part ways, the production line is yours to run.
Can this work with our existing DAM and workflow?
Yes. aiX delivers into the tools you already run — DAM, PIM, storefront, HubSpot — rather than adding another system your team has to check.
Implementation
aiAccelerate
Replatform in weeks, not quarters — and come out machine-readable.
aiAccelerate is AI-led commerce implementation: BigCommerce, Adobe Commerce, Shopify, and headless builds delivered 40–60% faster than traditional agency timelines, with agent-readiness built into the foundation instead of bolted on later.
The traditional replatform is a two-year program with a 30-person team, and most of that time is spent on work that is now automatable: content migration, template conversion, integration scaffolding, QA regression. aiAccelerate replaces the headcount with a small senior team running Claude and Claude Code through the delivery pipeline — engineers direct, the toolchain executes, and the savings in time and budget flow to you.
Speed is only half the point. Every aiAccelerate build ships machine-readable by default: structured catalog data, schema.org markup, clean feeds, crawlable policies, llms.txt. You come out the other side not just on a modern platform, but legible to the AI assistants your customers are already asking — the foundation GEOPro then measures and compounds.
We are a BigCommerce Diamond Partner and deliver on Adobe Commerce, Shopify, SCAYLE, Shopware, and headless stacks. Fixed scope, staged cutover, zero-downtime launch — the discipline of an enterprise integrator without the enterprise drag.
Delivery runs on Claude and Claude Code — the compression is the toolchain, not corner-cutting. Senior engineers review everything that ships.
Fixed-scope build plan
Priced, sequenced, and dated before work starts — scope changes are decisions, not surprises.
AI-accelerated delivery
Migration, integration, and QA run through Claude Code — 40–60% faster than traditional timelines.
Machine-readable foundation
Structured data, schema, feeds, and discovery files ship with the build, not after it.
Zero-downtime cutover
Staged launch with rollback at every gate — revenue does not pause for the migration.
01
Scope
Fixed price, fixed timeline, staged plan — agreed before the first commit.
02
Build
A small senior team delivers through the AI pipeline, with weekly working demos.
03
Cut over
Staged, reversible launch — then GEOPro baselines your new AI visibility.
Engagement shape: Focused replatforms run from 6 weeks; full enterprise builds 6–9 months. Every engagement is fixed-scope with staged gates — you always know where the build stands.
Where does the 40–60% actually come from?
From automating the work that used to be headcount: content and catalog migration, template conversion, integration scaffolding, test generation, and QA regression. A five-person senior team with Claude Code covers what previously took thirty people — and we price the engagement off the smaller team, not the old model.
Is an AI-built store production-grade?
The AI accelerates the pipeline; senior engineers own the architecture and review everything that ships. You get the same staged cutover, load testing, and rollback discipline as a traditional enterprise build — it just arrives months earlier.
Which platforms do you implement?
BigCommerce (Diamond Partner), Adobe Commerce, Shopify, SCAYLE, Shopware, and headless builds on modern frontends. If you are choosing between them, aiFocus or a 20-minute call with Justin will get you a straight recommendation.
Do we have to replatform to become agent-ready?
Often no — and we will tell you so. Much agent-readiness work is additive on your current platform. aiAccelerate is for when the platform itself is the ceiling: it cannot expose the data, performance, or flexibility the next five years require.
Marketing AI
aiEngage
Demand generation that runs itself — on the HubSpot you already own.
aiEngage turns your HubSpot stack into an AI-run demand engine: content, campaigns, scoring, and follow-up produced and orchestrated with Claude — measured by pipeline, not activity.
Most companies use a fraction of the HubSpot they pay for, and the gap is always the same: producing enough good content and follow-up to keep the machine fed. aiEngage closes that gap with an AI production and orchestration layer on top of your existing portal — campaigns drafted, personalized, and shipped with Claude; workflows, scoring, and routing engineered by people who build on HubSpot every day.
The engagements are unglamorous on purpose: clean the CRM data, fix attribution, build the nurture paths, automate the follow-up nobody sends, and publish content that answers what your buyers actually ask. Then measure it the only way that matters — meetings created and pipeline sourced, not email volume.
Because we also build the machine-readable layer, aiEngage campaigns compound with your AI visibility: the same answers that nurture a prospect are structured so assistants can cite them. Your marketing works on humans and agents at once.
Content and orchestration run on Claude inside your HubSpot portal — reviewed by marketers, measured by pipeline.
Portal foundation
CRM hygiene, attribution, scoring, and routing fixed — the plumbing demand gen depends on.
AI content engine
On-voice campaigns, nurtures, and answer-content produced with Claude and reviewed before send.
Lifecycle automation
Workflows that follow up, qualify, and route — every hour, without headcount.
Pipeline reporting
Dashboards that tie the motion to meetings and revenue — activity metrics retire.
01
Fix the foundation
Data, attribution, and scoring cleaned so automation has something true to run on.
02
Turn on the engine
Content and lifecycle automation ship in weekly increments, measured from day one.
03
Compound
The motion tunes itself on what converts — and feeds your AI visibility as it goes.
Engagement shape: Runs as an ongoing engagement with a fixed monthly scope, typically after a 4–6 week foundation sprint. You keep everything: workflows, content, and the portal are yours.
Does this replace our marketing team or our agency?
It replaces production drudgery, not judgment. Your team (or fractional leadership) still owns strategy and voice; aiEngage gives them a production and automation engine so the calendar ships. Most clients redirect agency retainer spend here and keep strategy in-house.
We already have HubSpot workflows. What changes?
Usually the foundation. We audit what exists, fix data and attribution first, then rebuild the lifecycle around what actually converts. The difference clients feel is follow-up that happens every time and reporting that ties marketing to pipeline instead of opens.
Is AI-generated content safe for our brand?
Everything ships through review gates — voice encoded first, human approval before send, and no autonomous publishing to customers. You get AI speed with the same editorial control you have today.
What results should we expect, and when?
The foundation sprint pays back first: attribution you can trust and follow-up that stops leaking. Pipeline movement typically shows in the first full quarter — and it is measured in meetings and sourced revenue, which is the report you will see.
FAQ
Frequently asked questions
What is agentic commerce, in plain terms?
It's what happens when customers delegate shopping to an AI assistant. The agent does the discovering, comparing, and increasingly the checkout — reading structured data instead of browsing pages. Agentic commerce is making your store legible and transactable to those agents, so you win the recommendation before a human ever sees a search results page.
Is my store agent-ready today — and how would I know?
Most aren't, and the quick self-test is telling: ask an AI assistant about your pricing and return policy and see if it answers accurately — or at all. The rigorous version is aiFocus: a fixed-scope audit that scores your catalog, data, and stack the way an agent reads them, benchmarks how assistants answer your category prompts, and hands you a sequenced, priced roadmap.
How long does an engagement take?
aiFocus assessments run 3–6 weeks. aiAccelerate implementations range from 6 weeks for a focused replatform to 6–9 months for a full enterprise build. aiX and aiEngage typically run as ongoing monthly engagements after a short foundation sprint. Everything is fixed-scope with staged gates — no open-ended programs.
Do you work on our existing platform, or is it a rebuild?
Existing platform first, always. Much of agent-readiness is additive — structured data, feeds, discovery files, content — on the BigCommerce, Adobe Commerce, Shopify, or HubSpot you already run. A rebuild only enters the conversation when the platform itself can't expose what agents need, and we'll show you that evidence in the aiFocus roadmap before anyone proposes one.
What does "machine-readable" mean for our catalog?
Products, pricing, inventory, and policies published in formats a model can parse and trust: schema.org markup, clean structured feeds, llms.txt discovery files, and crawlable pages — instead of data locked inside rendered templates, images, and PDFs. A human can squint at those; an agent just moves on to a competitor it can read.
How is Claude used in the work?
Delivery runs on Claude and Claude Code across all four services — engineering, migration, QA, content production, and campaign orchestration. A small senior team directs the toolchain instead of a thirty-person bench doing the work by hand; that's the 40–60% compression, and the savings price into your engagement, not our margin.