E-commerce Stores · AI Automation
AI Automation for E-commerce Stores That Actually Fits Your Catalog
Running an online store means your team is stuck writing the same product descriptions, answering the same shipping and sizing tickets, and watching generic recommendation plugins underperform against your actual margin goals. Off-the-shelf AI tools bolt on, but they don't know your SKUs, your return policy, your brand voice, or the Shopify/BigCommerce/WooCommerce stack you already run on. A Build Pod from Asaasin installs a dedicated AI engineering team inside your workflow — shipping automation that reads your product feed, your support macros, and your order history, then quietly does the repeat work so merchandisers, CX, and growth can focus on the decisions only humans should make.
What we build for E-commerce Stores
Generate on-brand product descriptions across the full catalog
Ingest supplier feeds, images, and spec sheets to draft SEO-ready PDPs in your voice, with attribute consistency across variants. Merchandisers review in bulk instead of writing from scratch.
Deflect repeat support tickets on shipping, sizing, and returns
Train an agent on your help-desk history, policy docs, and order data so it resolves WISMO, size-swap, and returns questions end-to-end in Gorgias, Zendesk, or Shopify Inbox — escalating only genuine edge cases.
Personalise on-site recommendations beyond the default plugin
Build a recommender tuned to your margin, inventory depth, and customer LTV — not just view-together heuristics — and wire it into PDP, cart, and post-purchase email surfaces.
How a Build Pod fits
A Build Pod is a small, dedicated team — typically a senior engineer, an AI specialist, and a product lead — that embeds with your merchandising, CX, and growth leads. Week one, we map your stack (Shopify, Klaviyo, Gorgias, your PIM, your 3PL feeds) and pick the one automation that will claw back the most hours. You see working software inside the first sprint, in your staging store, against your real catalog.
From there the Pod runs like an in-house squad on a monthly subscription: weekly demos, shared Slack, and a roadmap that flexes with peak season. As new SKU launches, BFCM prep, or platform migrations come up, the same Pod picks them up — so the automation compounds instead of being a one-off project that rots after launch.
Frequently asked questions
- How long before we see working software in our store?
- You'll see a working prototype against your real catalog or ticket history inside the first two-week sprint. Production rollout typically follows once merchandising or CX has reviewed the output quality.
- Do you work inside Shopify, BigCommerce, or headless stacks?
- Yes — Pods have shipped on Shopify and Shopify Plus, BigCommerce, WooCommerce, and custom headless setups using Next.js or Remix. We build against your existing admin, PIM, and helpdesk rather than asking you to migrate.
- Who owns the code and the models once we build them?
- You do. Everything the Pod ships lives in your repos, your cloud accounts, and your vendor contracts. If you ever pause the subscription, the automation keeps running.
- How do you handle brand voice and accuracy on generated product copy?
- We tune prompts and evaluators on a sample of your existing best-performing PDPs, then route drafts through a merchandiser review queue before publish. Voice drift and hallucinated specs are caught before they hit the storefront.
Ready to ship AI for e-commerce stores?
A Build Pod gets working AI into your stack in 2–3 weeks. Month-to-month, cancel any time.
Talk to a Build Pod