★★★★★
The automation was set up in a clean and practical way by the Checkout Loom team. It saved me a lot of manual work and made the whole process much easier.
JanoUnited Kingdom
Verified
AI Shopify agent
AI Shopify agent that handles order edits, address changes and draft orders so your order desk stops keying by hand
AI Shopify agent work starts at the order desk, where a team member reads an email asking to change an address, checks whether the order has been picked, edits it in the admin, tells the customer and notes what happened, and does this thirty times a day. We build an agent on n8n and the Shopify Admin API that reads those requests, verifies the buyer, applies the change only before your pick cut-off, creates draft orders from phone and email orders, and sends anything unusual to you with the facts, with a log you can reverse.
- Fixed price from $2,290, paid once
- Edits only before your pick cut-off
- Exceptions reach you with the facts attached
- Platforms supportedShopify Basic, Grow, Advanced and Plus, using a custom app, the Admin API, Flow and, where useful, Shopify’s MCP servers.
- Typical storeStores that receive many address changes, order edits, cancellations and phone or email orders that staff must key into the admin.
- Order volumeFrom a few hundred to tens of thousands of orders a month, with the agent sized to the number of requests and not the number of orders.
- Stores coveredThe price covers one Shopify store, and further stores or inboxes are added in the calculator.
- Build routesAn n8n workflow in your own account, a ready AI agent app for Shopify, or a mix, chosen from your volume and need for control.
- Live inTwo to four weeks for the standard agent and up to seven weeks with draft orders, B2B accounts and a voice line.
The costly disconnect
Why Shopify order desk work eats staff time even in a well-run store
Shopify takes the order automatically, but everything that happens to an order afterwards, such as a changed address, a swapped size, a cancelled item or a phone order, still passes through a person reading an email and clicking through the admin.
Edits that race the warehouse
An address change that arrives after the order has been picked is useless, so every hour of delay raises the chance of a lost parcel or a return. Left alone, this problem repeats with every order, which is why automation for ai shopify agent is built to handle it by rule and not by memory.
Requests buried in the inbox
Order changes arrive in the same inbox as everything else, and the urgent ones wait behind newsletters and invoices. It is easy to overlook until a busy week exposes it, and by then the cost to ai shopify agent is already counted in refunds, hours or lost sales in the automation work.
Edits made on the wrong order
Tired staff change the wrong line or the wrong order when requests are similar, and the error becomes a refund. The fix is not more effort but a better rule, and that is exactly what the automation build for ai shopify agent puts in place.
Phone and email orders keyed by hand
Trade and repeat customers who order by message need a draft order created, priced and invoiced, which takes a person ten minutes each time. Many owners only notice this problem when a customer complains, so catching it earlier is one of the quiet benefits of automation for ai shopify agent.
Identity checks done inconsistently
Some staff verify the buyer and some do not, so changes are sometimes made on the word of whoever emailed. Left alone, this problem repeats with every order, which is why automation for ai shopify agent is built to handle it by rule and not by memory.
No count of what the desk handles
Without categories, nobody knows how many requests are address changes and how many could be prevented by a better checkout. It is easy to overlook until a busy week exposes it, and by then the cost to ai shopify agent is already counted in refunds, hours or lost sales in the automation work.
- 30order requests a day is common for a store doing a few hundred orders a week, most of them address, size or cancellation changes.
- 100cost points a second is the standard GraphQL Admin API limit, which is ample for order desk work when requests are queued sensibly.
- 0edits should be applied after the pick cut-off, which is why the cut-off is the first rule we write.
Request counts come from order desks we have audited and are indicative; the rate limit is from Shopify’s developer documentation, checked at build time.
What changes at your Shopify order desk once an agent handles the routine requests
Requests are read, verified and applied in minutes before dispatch, and only the unusual ones reach a person.
How the order desk runs now
- Order change requests wait in the shared inbox.
- Staff edit orders by hand and sometimes on the wrong order.
- Phone and email orders are keyed into the admin.
- Identity checks vary by person.
- Nobody counts what the desk handles.
How it runs with the agent
- The agent reads each request within minutes and finds the order.
- Edits follow a fixed procedure that checks the order status and pick cut-off first.
- Draft orders are created from messages, priced from your rules and sent for payment.
- Every change requires the same identity check.
- A weekly report counts requests by type.
What the desk reports
- Fewer lost parcels from late edits.
- Fewer wrong edits.
- Less keying.
- Consistent verification.
- Data to fix the causes at checkout.
What the agent deals with
- Finding the order from the email address or order number.
- Checking fulfilment status and the pick cut-off.
- Updating addresses, sizes and quantities when the order is still editable.
- Creating draft orders from messages and sending the invoice link.
- Replying to the customer and writing a note on the order.
What reaches a person
- Requests that arrive after the cut-off.
- Changes that alter the price or shipping method.
- Customers who cannot be verified.
- Cancellations of shipped orders and any dispute.
- Anything the agent marks as uncertain.
Which Shopify merchants should put an agent on the order desk
If your team edits orders daily or keys in phone and email orders, the time saved is immediate and the risk of late edits falls.
Stores with a same-day pick window
A short window between order and pick makes quick, correct edits worth more. We look at this situation in the audit and give ai shopify agent an honest view of whether the build is worth doing now or later in the automation work.
Stores with custom or made-to-order items
Size, colour and personalisation changes arrive often and need checking against production status. If this describes your business, the automation work for ai shopify agent is likely to pay back quickly, and we will tell you plainly if it will not.
Stores with trade or B2B customers
Customers who order by email benefit from draft orders created from their message. Owners in this position often say the biggest change is the time returned each week, and automation is built to deliver that first for ai shopify agent.
Stores with many address errors
International checkouts produce address problems that can be caught and fixed before dispatch. This is the kind of situation where a fixed-price build is easier to justify than a monthly subscription for automation for ai shopify agent.
Stores with frequent exchanges
Size swaps and replacements follow a procedure that the agent applies consistently. We look at this situation in the audit and give ai shopify agent an honest view of whether the build is worth doing now or later in the automation work.
Teams that want fewer interruptions
Routine edits stop interrupting people who should be packing, buying or planning. If this describes your business, the automation work for ai shopify agent is likely to pay back quickly, and we will tell you plainly if it will not.
The Shopify events and requests that give the agent work
We use Shopify webhooks for order state and an inbox trigger for requests, and we pair them so every request meets the latest facts.
orders/updatedThe order changes
Fulfilment, tags and edits are watched so the agent always acts on the current state. The timing of this step is written down in the rule table, which means you can change when it happens without asking us to rebuild anything in the automation build for ai shopify agent.
fulfillment_orders/updatedThe order is picked
A pick or hold status closes the edit window for that order and moves later requests to a person. If the same event arrives twice, the second copy is recognised and ignored, so automation for ai shopify agent never repeats an action by accident.
email_receivedA customer asks for a change
The agent classifies the request, finds the order and starts the matching procedure. A short summary of how often this event occurs appears in the weekly report, giving ai shopify agent a clear view of how busy this part of the automation work is.
draft_order_requestedA buyer orders by message
The agent builds a draft order from the message and your price rules and waits for approval. Where the event depends on outside data, the data is checked for freshness first, because a stale figure is worse than no figure for automation for ai shopify agent.
payment_pendingA draft order awaits payment
The invoice link is sent, reminders follow within limits and the draft expires on your schedule. Each moment like this has its own rule, so automation for ai shopify agent behaves the same way every time and never has to guess what to do next.
approval_decisionYou approve or decline
Your decision applies the change or closes the request, and the customer is told either way. The event is logged with the rule that handled it, which lets you check later exactly what automation did for ai shopify agent and why it did it.
One address change followed from the customer email to a confirmed update
This shows the agent applying a routine edit safely and stopping where it should.
- 01
The request arrives
A customer emails to say they typed the wrong flat number on their order from yesterday and asks for it to be corrected. Timing for this step is paced to the limits of your tools, so automation for ai shopify agent keeps running calmly even when volume is high.
- 02
The buyer is verified
The agent matches the sender’s email to the order and, because it matches, treats the request as coming from the buyer. A check at the end of the step compares the result with the input, which catches the small mistakes that otherwise surface days later in the automation build for ai shopify agent.
- 03
The status is checked
It reads the fulfilment status and sees the order is not yet picked, which means the address can still be edited. Because the steps are separate, a change to one of them, such as a new rule for ai shopify agent, does not disturb the others in the automation flow.
- 04
The edit is applied
The agent updates the shipping address through the Admin API, stores the old address in the order note and tags the order as edited. The same step is repeated for every item in the batch, so the tenth record receives the same care as the first when automation runs for ai shopify agent.
- 05
The customer is told
A confirmation shows the new address and says it was changed before dispatch, in your tone. Anything unusual at this point is flagged in plain words, which saves you from reading logs to understand what the automation work found for ai shopify agent.
- 06
The log is written
The request, the check, the edit and the confirmation are recorded, and the weekly report counts it as an address change. At the end of this stage you can pause, adjust a rule or carry on, so automation for ai shopify agent always moves at the pace that suits you.
Pricing
Price your AI Shopify agent
Choose a plan, tell us which desk jobs the agent should take, and add any extras, and the total and live date update as you go.
What an AI Shopify agent costs and what raises the price
Our fee is fixed and paid once, while model usage, n8n hosting and any voice line are billed by their own providers.
Number of request types
Address changes, size swaps, cancellations and draft orders each add a procedure and tests. This is one of the factors we price in writing before work starts, so the automation quote for ai shopify agent reflects your real situation and not an average.
B2B and company accounts
Price lists, terms and company contacts add rules and checks. If this factor is small for you, it adds little to the price, and the written quote shows exactly how much it did add for ai shopify agent in the automation work.
Tools to connect
A warehouse system, a courier portal or a CRM adds an integration. You can lower the cost by tidying this part first, and we say so plainly in the plan when the automation work for ai shopify agent would benefit.
Languages
Each language multiplies the wording and the test requests. Anything extra that this factor creates later is quoted before it is built, so the fixed price for automation never grows by surprise for ai shopify agent.
Voice line
An inbound voice line adds telephony, a script and consent notices. We explain this factor in the quote in plain words, because ai shopify agent should understand what drives the price before agreeing to anything in the automation work.
Reporting depth
Custom dashboards and cause analysis take extra build time. Changes to this factor after the quote are handled as a written change, with its own price, and never as a hidden charge on automation for ai shopify agent.
Model usage, n8n hosting, telephony and Shopify apps are billed by those providers.
Next step
Ready to price AI Shopify Agent?
An AI Shopify agent runs your order desk by reading customer requests, checking the order in Shopify, applying edits, address changes and draft orders through the Admin API within your rules, and passing exceptions to you with the facts, built on n8n or a platform of your choice.
- One fixed price from $2,290, paid once
- Edits stop at your pick cut-off
- Thirty days of corrections included
Three more order desk jobs the same agent can take on
Once the agent can find and verify an order, other desk jobs follow the same procedure.
Draft orders for B2B reorders
A repeat trade buyer emails a list and receives a priced draft order and invoice link for approval. Because the groundwork for automation on ai shopify agent already exists, this extra job needs very little new work and is quoted in writing before it starts.
Cancellations before dispatch
Cancellation requests on unpicked orders are applied with a refund note, and shipped ones go to a person. The same records and rules that power automation for ai shopify agent are reused here, which keeps the cost low and the results consistent with the rest of the build.
A voice line for order questions
An AI voice agent for Shopify can answer your phone line with order status and pass changes to the written process. You can switch this job on later without rebuilding anything, so ai shopify agent can start with the core automation work and grow when the time is right.
Which Shopify data the agent reads and writes and where each fact is the source of truth
The agent runs as a custom app, and we list every scope and every field it may change before installing it.
| Store object | Fields we use | Direction | Source of truth |
|---|---|---|---|
| Orders | Status, items, address, tags, notes | Read and edit before the cut-off | Shopify orders |
| Fulfilment orders | Status, location, hold | Read only | Shopify fulfilment |
| Customers | Email, name, company, history | Read for verification | Shopify customers |
| Draft orders | Lines, prices, discounts, status | Created and updated | Shopify draft orders |
| Requests | Sender, type, outcome, time | Written by the agent | Desk log |
| Change history | Field, old value, new value, rule | Written on every edit | Agent action log |
Customer fields fall under Shopify’s protected customer data levels, so the app requests only those the desk procedures need.
Edge cases at the order desk that we test before launch
Order edits go wrong at the edges, so we rehearse them on a development store with copies of your real requests.
Requests that arrive at the cut-off
A request received seconds before a pick run is treated cautiously and handled by a person if the status is uncertain. Cases like this are the reason the automation build for ai shopify agent includes a trial run, because a tidy example never shows them but real records do.
Emails from someone else
A sender who does not match the order is asked for the order number and, failing that, passed to a person. Your answer to this case is added to the rule table, so the same situation is handled automatically the next time it appears for ai shopify agent in the automation work.
Orders edited twice
Two requests on one order are queued and applied in order, with the second checked against the first. The weekly report counts how often this case occurs, which tells ai shopify agent whether it deserves a better rule or is simply rare in the automation work.
Split fulfilments
Orders that ship from two locations are edited only for the parts still unpicked. Nothing about this case is hidden from you: it appears in the log with the date, the record and the rule that dealt with it in the automation build for ai shopify agent.
Address formats by country
Addresses are validated against the country format and flagged when they look incomplete. We list the cases that matter most for automation in your handover guide, so anyone on your team can understand how ai shopify agent deals with them.
Price-changing edits
Any edit that changes the total or the shipping method goes to you for approval, whatever the customer asks. A rule for this case can be tightened or relaxed in minutes in the rule table, without waiting for a rebuild or a new quote in the automation build for ai shopify agent.
Doing it by hand, an AI agent app for Shopify and a built n8n agent compared
Staff will always be needed, an AI agent Shopify app is quick to try, and a built agent on n8n gives the most control over procedures, cut-offs and data for stores with their own rules.
| By hand | Agent app | n8n build by us | |
|---|---|---|---|
| Handles requests around the clock | – | ✓ | ✓ |
| Respects your pick cut-off exactly | Partly | Partly | ✓ |
| Verifies the buyer the same way each time | – | Partly | ✓ |
| Creates draft orders from messages | Partly | Partly | ✓ |
| Data and logic stay in your accounts | ✓ | – | ✓ |
| Cost pattern | Staff time | Monthly plan | A single build fee, then hosting and usage |
Where a ready Shopify agent app already fits your procedures we say so, and we build on n8n only for the parts it cannot do.
How the Shopify agent is built and what each part costs
We choose the route that fits your volume and write down the monthly cost of each part next to our fixed fee.
n8n workflows
The Shopify and Shopify Trigger nodes watch order events, an AI agent node reads requests and calls tools, and error workflows catch failures. We choose the lightest option that does the job for ai shopify agent, since a simpler layer means fewer things to maintain and fewer ways to fail in the automation work.
A custom Shopify app
A private app with the narrowest Admin API scopes for orders, fulfilment orders, customers and draft orders. If you already pay for something that covers this need, we use it, and we only add a new service when automation for ai shopify agent genuinely requires one.
Shopify MCP servers
Where they fit, the Storefront MCP for catalogue and cart and the Customer Accounts MCP for authenticated order data, which needs a custom domain and OAuth. Access to this layer is granted from your own account and can be removed at any time, so you stay in control of the automation build for ai shopify agent.
A language model
A current model that classifies requests and drafts replies, while code applies the edits under your rules. Its limits and prices are checked again at the start of each project, because tools change their plans, and ai shopify agent should not pay for last year’s terms in the automation work.
Inbox and Slack
Gmail or Outlook labels as the intake and Slack or email for approvals and the stop switch. Everything this layer does for automation is logged, so you can see what ran, when it ran and what it cost on any given week for ai shopify agent.
A voice option
An inbound voice line answered by an AI voice agent for Shopify, with a spoken notice that the call is automated. We test the layer on your own data before launch, so automation for ai shopify agent is proven on real records and not on tidy examples.
How we keep an order desk agent correct on a live store
On a live order desk, correctness depends on checking state at the last moment and on being able to undo.
State checked at the last moment
The agent re-reads the fulfilment status immediately before every edit, not when the request arrived. Because this protection is written as a rule and not as a habit, it keeps working when staff change or the business gets busier in the automation build for ai shopify agent.
Stored previous values
The old address, quantity or line is stored with each edit so it can be reversed. When something goes wrong in automation for ai shopify agent, the failure is named, retried within safe limits and listed for you, instead of vanishing into a log nobody reads.
Webhook monitoring
Shopify retries a failed webhook up to eight times in four hours and then removes the subscription, so we watch for removal and rebuild it. This safeguard runs on every batch and not only on a schedule, so a problem in automation is caught before it can spread to the next record for ai shopify agent.
Alerts that name the order
Each alert gives the order, the request and the cause. Each alert names the rule, the record and the next step, which means you can fix the cause from the message alone without opening any tool in the automation build for ai shopify agent.
Rehearsal on a development store
Every procedure runs against copies of real requests before it touches your live orders. We compare the results of automation with your own records on a regular basis, so a small drift for ai shopify agent is repaired before it becomes a large one.
Owner explanations in writing
Any mistake in the first month is explained to you in writing with the fix. If a check fails, nothing is sent or changed for that record, and it waits in a short list for you, because a delay costs less than a wrong action in the automation build for ai shopify agent.
Scopes, protected data and control for a Shopify order desk agent
The agent can change orders, so its access is small, logged and easy to switch off.
Least-privilege scopes
We request only the scopes the desk procedures need and show you the list before installing. At the end of the engagement you receive a list of every connection that was made, so nothing stays open by accident in the automation build for ai shopify agent.
Protected customer data respected
Names, addresses and emails are accessed under Shopify’s protected customer data levels and only for the tasks that need them. For automation on ai shopify agent, access is limited to what the job needs and can be withdrawn in a minute, so ending the work leaves nothing behind.
App owned by you
The app lives in your store, so uninstalling it ends every connection at once. Nothing in this arrangement requires you to share a password, because access is granted from your own account in a form you can revoke in the automation build for ai shopify agent.
Minimal data to the model
The model sees the request text and the order facts needed, never card details. We keep no copy of your keys, records or customer details in systems that belong to us, and the handover guide shows you how to confirm that in the automation build for ai shopify agent.
Voice and consent rules
Callers are told the voice is automated, and we do not use AI voices for outbound calls without consent, in line with the FCC’s 2024 ruling. Only the fields that automation needs are read, and only for as long as the task takes, which keeps the exposure for ai shopify agent as small as it can be.
Tidy handover
You receive a list of every connection and we delete our own access on the last day. Every access is logged in your own accounts, so you can see who or what touched a record and when, without asking us for a report in the automation build for ai shopify agent.
What you receive with your AI Shopify agent
Each plan ends with a working agent, written procedures and a log you own.
- A private Shopify app limited to the scopes the desk needs, with each scope explained in writing.
- Request intake from your inbox with classification and order matching.
- Address, size and quantity edits applied only before your pick cut-off.
- Identity checks written into every procedure.
- Draft orders from phone and email requests, with invoice links and reminders.
- Approval messages for price-changing edits and exceptions.
- A change log with old and new values and a one-step reversal.
- A weekly report of requests by type.
- A month of corrections after the agent is live.
Verified client reviews and the platform limits behind our order desk builds
These are the unedited words of verified clients of the Checkout Loom team, followed by the Shopify facts our agent designs rely on.
- 8attempts across four hours is how long Shopify keeps retrying a failing webhook, which is why our desk agent has a daily check that every subscription still exists.
- 100cost points a second is the standard GraphQL limit, and Plus stores receive ten times that.
- 30 daysof corrections run from the launch date, which is long enough to see the desk through a full order cycle.
The webhook retry window and the GraphQL rate limit come from Shopify’s developer documentation and are verified again when we build.
★★★★★
I highly recommend ordering from the Checkout Loom team. I had slow responses and poor communication with other providers, but this team was great and I am very happy with their service.
HarmetUnited States
Verified
★★★★★
I am a returning customer because my first AI automation workflow worked so well. Once again everything was built exactly as requested, and the whole process was reliable from start to finish.
WilliamUnited States
Verified
★★★★★
The determination and commitment to quality from the Checkout Loom team were clear from day one. They understood my requirements perfectly and completed everything with professionalism and care, and it is rare to find a team this dependable.
LorcanColombia
Verified
★★★★★
It was an excellent experience from start to finish, and the automation works reliably with everything configured properly. It is clear that the team has strong knowledge of automation, and I will definitely be returning for future work.
EllieUnited States
Verified
★★★★★
The team carefully investigated the problem, tested different scenarios and delivered a dependable solution. A duplicate contact issue had been causing problems for quite some time, and it is finally resolved.
RichardUnited States
Verified
★★★★★
The Checkout Loom team were easy to work with and brilliant at the work itself. I highly recommend them to anyone who needs dependable automation.
IveraAutomation client
Verified
★★★★★
Everything was configured exactly as discussed, and the team made sure the automation was stable before delivering it. It has been a huge time-saver for our whole team, and it runs without any manual work.
BellamyUnited States
Verified
★★★★★
This was excellent automation work, and it is clear that the team has strong experience with AI and automation. I highly recommend the Checkout Loom team to other businesses.
FinnUnited States
Verified
How the Shopify agent build runs from request audit to supervised launch
We start from your real requests, because they show which procedures the desk follows today.
- 01
Audit the requests
We read a month of order change emails and group them by type, cause and the action your team took. Nothing in this step touches your live customers, so ai shopify agent can review it calmly and ask for changes before anything goes public in the automation work.
- 02
Write the procedures
We write the check, the cut-off and the action for each request type and agree them with you in writing. The step has a clear finish line, which means you always know whether the automation work for ai shopify agent is on time or running behind.
- 03
Install a scoped app
We create a custom app with the narrowest scopes and connect it to n8n or the platform you chose. Questions that arise here are answered in writing, so there is a record of every decision made about automation for ai shopify agent.
- 04
Rehearse on a development store
We run copies of real requests through the agent and compare each outcome with what your team did. We keep each step small enough to check, because large steps hide mistakes and make the automation build harder to correct for ai shopify agent.
- 05
Supervised launch
The agent drafts every action for approval at first and then applies the safest request types alone. At the end of this step you approve or ask for changes, and the next stage of automation starts only after your reply for ai shopify agent.
- 06
Hand over
You receive the procedures and the log with a month of corrections, and we remove our access. The time this step takes depends on how quickly your records and answers arrive, and we tell ai shopify agent early what we need to keep moving in the automation work.
Estimate the order desk time an AI Shopify agent could return
Enter how many order requests your desk handles and the estimate shows the staff time released by the share the agent takes over.
Requests handled each week–
Staff hours released each week–
Value of that time each year–
The estimate counts only desk time, and the value is a planning figure that ignores fewer lost parcels and refunds from faster edits.
AI Shopify agent questions, answered in full
These are the questions Shopify merchants ask about agents, n8n, apps, voice and cost before they order.
What is an AI Shopify agent?
It is an agent that works your order desk through a custom Shopify app, reading customer requests, verifying the buyer, applying edits and creating draft orders within your rules and cut-offs, and passing exceptions to you with the facts.
Is there an AI agent Shopify app I can install instead?
Several exist, and an AI agent Shopify app can be a good start for simple cases. We compare them with a built agent on your procedures, your cut-off and where your data sits, and we recommend whichever fits at the lowest long-term cost.
Can you build a Shopify AI agent on n8n?
Yes, a Shopify AI agent n8n build uses the Shopify and Shopify Trigger nodes to watch orders, an AI agent node to read requests and call tools, and error workflows to catch failures, hosted in your own n8n account or on n8n cloud.
How does the agent avoid editing an order that has been picked?
It re-reads the fulfilment status immediately before each edit and stops if the order is picked, on hold or partly fulfilled, then tells the customer the truth and sends you the thread.
How does it verify who is asking?
It matches the sender to the email on the order and asks for the order number when they do not match, and changes that affect the price or the delivery method always wait for your approval.
Can you set up an AI voice agent for Shopify?
Yes, as an option, an AI voice agent for Shopify can answer your phone line with order status and pass any change to the written process. Callers hear that it is automated, and outbound AI voice calls are not used without consent.
Can it create orders from emails and phone messages?
It creates draft orders from the message, prices them from your rules, sends the invoice link and waits for your approval, so you no longer key trade and repeat orders by hand.
What access does the agent need?
A custom app with the narrowest Admin API scopes for orders, fulfilment orders, customers and draft orders, which you install and can remove at any time, and access to the inbox labels it works in.
How soon does the Shopify agent start and what must I hand over first?
The standard agent is usually live in two to four weeks. We need a month of order change emails, your pick cut-off and procedures, the ability to install a custom app and a development store or permission to create one, and we send a written checklist after you order.
What will it cost me every month?
Our fee is charged once, while language model usage, n8n hosting and any phone line are billed by their providers, and we estimate that monthly cost in writing for your request volume before you decide.
Let an agent handle the order changes while your team packs and ships
Choose a plan in the pricing calculator and continue to checkout, or request a quote describing the order changes your desk handles and your pick cut-off. We reply in writing within one working day with a confirmed start date and a short checklist, so the request audit begins straight away.
- One fixed price from $2,290, paid once
- Edits stop at your pick cut-off
- Thirty days of corrections included