AI workflows for ecommerce and DTC teams
Koya places trained AI automation developers into businesses full-time to build internal tools, automate manual workflows, and help your team move faster without adding more headcount.
Our developers build around your actual tools, team, and workflows. The examples below show the kinds of projects they could take on.
Examples of systems our AI automation developers could build
These are example builds for ecommerce and DTC teams. Your developer would scope the real version around the tools, data, and approval steps you already use.
Order exceptions flagged before they become support tickets
This system watches orders after checkout and flags the ones that need attention before customers start asking what happened. It is built for brands where Shopify, the WMS, 3PL updates, support tickets, spreadsheets, and warehouse notes do not always stay aligned.
- 01 The workflow pulls orders from Shopify, the WMS, the 3PL portal, shipping tools, support inboxes, and internal spreadsheets.
- 02 The system checks for stuck orders, delayed shipments, missing tracking, failed fulfillment, address issues, high-value orders, VIP customers, and orders split across locations.
- 03 It matches each issue with the latest available context: payment status, fulfillment status, tracking events, stock availability, customer history, and internal notes.
- 04 It ranks exceptions by customer impact, age, order value, and whether the customer has already contacted support.
- 05 The team gets a daily queue with the issue, recommended next step, and a draft customer update where needed.
The ops team stops finding fulfillment problems through angry customer emails. Delayed, stuck, or messy orders are surfaced in one queue, with enough context for the team to fix the issue or update the customer quickly.
Stock risk surfaced before promos, fast sellers, and wholesale orders create gaps
This system helps the team spot stock risk across Shopify, warehouse data, 3PL feeds, supplier sheets, bundles, subscriptions, and upcoming promotions. It is useful when inventory decisions still depend on someone checking Shopify, spreadsheets, and warehouse updates by hand.
- 01 The workflow pulls SKU-level stock, sales velocity, open orders, bundle rules, subscription demand, supplier lead times, and incoming POs into one view.
- 02 The system compares available stock against recent sales, forecasted demand, upcoming promos, wholesale commitments, and reorder rules.
- 03 It flags fast sellers, low-stock SKUs, overstocked items, delayed inbound inventory, and items likely to block a bundle or subscription order.
- 04 It ranks priority issues by revenue impact, customer impact, and how soon action is needed.
- 05 The team receives a daily or weekly replenishment brief with suggested checks, reorder needs, and risky SKUs.
Inventory review moves from scattered checks to a focused decision list. The team sees stock risk early enough to reorder, adjust promos, swap bundle components, update merchandising, or warn customers before the issue hits revenue.
Support and returns handled with order status and policy context already pulled in
This system drafts support replies and return decisions using the customer's actual order data, tracking status, return rules, product information, and prior conversation history. It is built for teams handling repeated questions about delivery, refunds, exchanges, damaged items, wrong items, cancellations, sizing, subscriptions, and product fit.
- 01 The workflow classifies incoming tickets by issue type: order status, refund, return, exchange, damaged item, wrong item, cancellation, subscription, product question, or escalation.
- 02 The system pulls the customer's order, tracking events, fulfillment status, refund history, product details, return policy, and any VIP or subscription rules.
- 03 It checks whether the request meets policy, whether a warehouse or 3PL action is needed, and whether the customer should be escalated to a human.
- 04 It drafts the reply in the brand's tone and prepares the next action: replacement, refund review, exchange, return label, subscription update, or escalation.
- 05 Support reviews the draft and sends it, with every decision logged for future reference.
Support spends less time jumping between tools to answer the same questions. Customers get faster, more consistent replies, while edge cases still go to a person with the relevant order and policy context already attached.
One daily view of the orders, stock, support, and channel issues that need attention
This system gives the team one daily view of the numbers and exceptions that usually live across Shopify, support, warehouse tools, spreadsheets, ad platforms, and channel reports. It is designed for brands where the founder or operator still checks multiple tabs to understand what needs attention.
- 01 The workflow pulls orders, revenue, refunds, returns, support volume, fulfillment status, stock risks, subscription issues, paid-channel spend, and warehouse updates into one reporting layer.
- 02 The system cleans and standardizes the data so the team can compare the same metrics each day.
- 03 It flags unusual changes: refund spikes, support-ticket surges, delayed fulfillment, SKU stock risk, ad spend shifts, channel underperformance, or warehouse backlog.
- 04 The founder or operator gets a short daily brief with the metrics that changed and the issues that need a decision.
- 05 The dashboard keeps a running history so recurring problems can be reviewed weekly instead of rediscovered one by one.
The team stops relying on tab-checking and spreadsheet stitching to know what is happening. The business gets one place to review daily operations, spot problems early, and decide what needs attention before small issues spread across support, fulfillment, and revenue.
What clients say about Koya developers
Joshua quickly became a key part of our team. He handles complex automation tasks across several client projects, freeing us up to focus on strategy. The process was smooth, and Joshua's skills and communication have been spot on. We're excited to bring on more developers like him as the business grows.
Koya made the process easy to get started. We were paired with an AI automation developer whose experience and past projects we reviewed in his portfolio. He has now been on our team for 9 months, and I'd definitely recommend Koya to any business looking to improve its operations.
Start with one workflow, built on the house
You see the work before any commitment. We handle recruiting, payroll, compliance, and coaching.
- 01 You pick a workflow, or we help choose one on the call
- 02 We scope the first build around your tools and process
- 03 A Koya developer builds that workflow on the house
- 04 If you want to bring them on full-time to build more, the placement starts with a 30-day trial window
- 05 If it's a fit, the developer continues as full-time automation capacity for your team
Ready to see what this could look like inside your business?
On the call we pick one workflow, scope it around your tools, and a Koya developer builds it for free. You decide what happens next.