Trusted by companies across the USA
Store builds and checkout work shipped in days, not weeks
A founder came to us with a Shopify store that took 30 seconds to render its collection page and a checkout that dropped one in four buyers. We rebuilt the front end and the Stripe flow in nine working days, not the five weeks the last quote estimated. That speed comes from pairing experienced developers with the best available AI coding tools.
We match you within 48 hours.
Trusted by companies across the USA
A skincare brand on WooCommerce asked us to fix a checkout that kept timing out during their Friday email drops. Their old developer had quoted six weeks to migrate the cart and rework the Stripe integration. We rebuilt the cart logic and moved their payment flow to a cleaner Stripe Checkout setup in eleven working days. The store handled 1,400 orders the next Friday with no timeouts.
That pace is the point of this model. An AI-Powered E-commerce Developer is one of our senior engineers working with the best available AI coding tools. The tools draft boilerplate, scaffold React components, write the first pass of tests, and surface API edge cases the engineer reviews. A typical Shopify or WooCommerce build that used to run three weeks now lands in eight to ten days.
The hourly is higher than a standard developer, but the total usually comes out lower because the work finishes in roughly half the calendar time. Fewer billed hours on the same scope is the math that matters, and we show it against your feature list before you commit. This is not staff augmentation by the seat. You are buying throughput on a defined build.
Here is the honest part. AI tooling speeds up the pattern-heavy work: product templates, REST API connectors, cart and checkout scaffolding, migration scripts, test coverage. It does not speed up the parts that need judgment. Deciding how inventory syncs across three channels or debugging a webhook race condition still takes a person thinking carefully.
The tools generate the first version of a React product grid or a Stripe webhook handler in seconds. Our engineer reads every line, fixes what is wrong, and keeps what holds up. No code ships unchecked.
This model fits Shopify theme rebuilds, WooCommerce migrations, custom checkout flows, and headless React storefronts. The work is concrete and feature-driven, so the throughput gain shows up clearly.
A collection page redesign that took 12 hours of hand-coding now takes closer to 6. The saved time goes into testing and polish, not into hours you did not need.
Every pull request gets read by the engineer who owns it before it touches your store. Payment code near Stripe and order data gets a second pass. A suggestion is a draft, not a decision.
You pay more per hour and fewer hours overall. On a defined build the calendar time drops by close to half, so the same feature list costs less.
Our team works from India and overlaps your US business hours for calls and reviews. You hand off requirements at end of day and wake up to a deployed staging build.
A WooCommerce-to-Shopify migration a single developer would spread across five weeks tends to finish in two to three here. The AI tools handle the repetitive data mapping and template conversion while the engineer focuses on the parts that break. You see a working staging store far earlier.
When the tools scaffold a React checkout component and write the first round of tests, the engineer spends the hour reviewing and refining instead of typing from scratch. That shifts more finished, tested work into every billed hour. The gain is largest on pattern-heavy work like templates and REST API connectors.
AI-assisted testing catches edge cases a rushed developer skips: an empty cart, a declined card, a SKU with no inventory. The engineer reviews the generated tests and adds the ones the tools miss. You end up with more coverage on a Stripe flow than a hand-coded build usually ships.
The hourly is higher, but the calendar time on a defined scope drops by close to half. Fewer billed hours on the same feature list is where your total comes out lower. We map the hours against your build before you sign.
AI-powered developer working 40 hours/week on your project.
Same AI-powered developer, 20 hours/week. Consistent AI-augmented progress.
Pay for hours worked. Code reviews, sprints, or consulting with AI-powered output.
Hire a complete AI-powered team. Developer + designer + QA + PM, all using the best AI tools. Maximum output, one monthly rate.
This is the day-to-day delivery workflow, not the hiring process.
Get StartedWe start by listing every feature, integration, and edge case: which channels sync, how Stripe should handle subscriptions, what happens to abandoned carts. This is a human conversation over a call, not an AI task. The output is a scope we both agree on before any code is written.
With the scope set, we use AI tooling to sketch the data model, draft the API contracts, and surface integration risks early. The engineer reviews each suggestion and rejects what does not fit your platform. You get an architecture plan in a day or two instead of a week.
Here is where the tools earn their keep. They scaffold React components, write WooCommerce hooks, and draft your Stripe integration while the engineer reviews and corrects in real time. You see deployed staging builds every few days, not weeks later.
AI generates a broad test suite covering declined cards, empty carts, and inventory edge cases, then a person runs the payment flow manually to catch what automated tests miss. Anything touching Stripe or order data gets reviewed twice. Generated tests never stand in for a human checking that real money moves correctly.
We deploy during a low-traffic window, watch the first real orders flow through, and fix anything the live environment surfaces. After launch we stay on for quick iterations: a checkout tweak, a new shipping rule, a reporting fix.
Send us your feature list and we will map an AI-Powered E-commerce Developer against it: the timeline, the estimated hours, and the total compared to a standard build. You see the math before you decide, and you own all the code.
Describe your project and requirements.