AI support desk for wholesalers and B2B distributors
A distributor’s client questions are massively repetitive: stock, lead time, net price, where is my order, resend the duplicate. The agent answers them alone by reading your ERP, at the client’s own net price, and passes judgment calls to order processing.
In your day-to-day
- 01
Immediate answers on availability and restocking lead time, item by item.
- 02
Quoting the client’s net price — their grid, their discounts — without going through the rep.
- 03
Sending duplicate invoices and delivery notes on simple request, in the right format.
A typical scenario
An electrical-supplies distributor runs three branches and a six-person order desk that fields 200 requests a day — stock, lead times, net prices, duplicates.
- 01
By 7:40 the twelve overnight requests are closed: availability confirmed, duplicates sent, three ambiguous cases queued with a draft reply.
- 02
A site foreman wants “whatever you have in stock” to replace an out-of-stock reference: the agent offers the catalogue-approved substitutions, with the account’s net price difference.
- 03
Friday 5:50 PM, a question about a backorder: the answer goes out with the restocking date confirmed by the supplier’s acknowledgement — nobody stayed late for it.
What changes
The order desk stops being a switchboard. The six clerks handle exceptions, disputes and emergencies; the repetitive flow resolves itself, outside opening hours included.
Order of magnitude
Working assumptions
- →200 requests a day, 70% of which concern availability, lead times, prices or documents
- →an average of 4 minutes of handling per request
Absorbing those 140 daily requests represents more than 9 hours of desk work a day — a full position redeployed to accounts and disputes.
Indicative estimate built on average sector assumptions — it gets recalibrated on your actual volumes during scoping.
What eats your days
- →
Orders arrive by email, WhatsApp and phone — and get retyped by hand into the ERP, with the errors that come with it.
- →
Client balances slip because collection comes after order processing, and the rep discovers the blocked account in front of the client.
- →
Supplier shortages and backorders surface at picking time — too late to offer an alternative.
How it works
- 1
The agent learns your business
It is fed your real sources: FAQ, documentation, ticket history, business rules. It only answers what it can source — no improvising.
- 2
Autonomous resolution, fenced
Recurring requests — tracking, invoices, procedures — are resolved end to end. Anything outside the fence goes to the human queue with a sourced draft reply already written.
- 3
Supervision and continuous improvement
Every conversation is reviewed by our engineers in the first weeks. The autonomous-resolution rate rises as the agent earns reliability — never the other way round.
Typical results
60%
of tickets resolved with no human involved, observed in production
3 min
first response, 24/7
×3
handling capacity for the same team
Orders of magnitude observed in production; your diagnostic sets your own baseline and targets.
Frequently asked questions
Does the agent know each client’s specific net prices?+
Yes: it reads the pricing conditions in your ERP — grids, discounts, running promotions — and never quotes a price that does not match the requesting account.
What does it do when an item is out of stock?+
It states the real restocking lead time and, if you authorise it, offers the substitutions you have validated in the catalogue. A sensitive request goes to the rep with context.
Is this the problem eating your team’s time?
Tell us how you work today — 30-minute call, then a free written diagnostic of what this agent would change for you, with numbers.
Get my free diagnosticFree resource
Get the self-assessment grid for your sector
Sales, admin, support, operations: the 20 tasks AI agents already handle in SMEs — with, for each one, the tell-tale sign that your team is concerned.