Take more orders without re-keying every one.
Distributors still receive a large share of orders as emails, PDFs and phone notes, then key them into the ERP line by line. We look for the workflows where agents read, match and prepare the work against your price lists and stock, with checks that stop a wrong price or a wrong quantity before it ships, and people keep the commercial calls.
Six workflows that grow with every new customer.
These are the workflows we would examine first in a wholesaler, distributor or B2B supplier. They run through the ERP or WMS, shared inboxes, supplier portals, EDI, customer-specific price lists and a lot of spreadsheets.
| Workflow | Manual today | AI-native version | Stays human | Verification check |
|---|---|---|---|---|
| Order intake from email and PDF | Inside sales reads each order, finds the customer, maps their part numbers to yours and keys the lines into the ERP. | An agent reads the order, maps customer part numbers, applies the customer's price list and creates a draft sales order. | New customers, unknown items, special terms and orders above a value limit. | Every line maps to a valid item and unit of measure. Prices match the customer's contract. Quantities fall inside normal ranges for that customer. |
| Quotes and special pricing | Sales builds quotes from price lists, margin sheets and past deals, then waits for a manager to approve discounts. | An agent drafts the quote from your pricing rules and history, and shows the margin on every line. | Discounts outside the agreed band and strategic accounts. | Margin floor per line and per quote. Quote validity dates and currency checked before sending. |
| Supplier order confirmations | Buyers compare each supplier confirmation with the purchase order and chase changes to price, quantity and dates. | An agent compares confirmations with the PO, flags differences and updates expected dates where you allow it. | Price increases, substitutions and supplier disputes. | Any price or quantity change against the PO is held for a buyer. Date changes update customer promises only through a rule. |
| Backorders and delivery date questions | Customer service checks stock, open POs and transport status, then answers "when will it arrive" by email or phone. | An agent answers status questions from the ERP and warehouse data and proposes partial shipments or alternatives. | Allocation of scarce stock between customers and alternative products with a price impact. | Promised dates must come from system data, not estimates. Alternatives must be approved substitutes. |
| Deductions and short payments | Credit control works through customer deductions, damaged goods claims and pricing disputes one remittance at a time. | An agent matches each deduction to the invoice, delivery proof and claim, then classifies it as valid, invalid or unclear. | Credit decisions, write-offs and credit limit changes. | Deduction reason codes must match the evidence. No credit note is issued without approval above a set amount. |
| Supplier product data | Product teams copy supplier spreadsheets into the item master and fix units, pack sizes and descriptions by hand. | An agent normalizes supplier data into your item schema and flags missing or conflicting attributes. | New product categories, hazardous goods classification and final item approval. | Every item passes the schema, unit and pack-size rules before it can be ordered or sold. |
Six numbers that show whether it worked.
The Audit measures these before anything is built. The Pilot is measured against the same numbers.
| Metric | Definition |
|---|---|
| Minutes per order line | Total people time from order receipt to confirmed sales order, divided by order lines entered. |
| Order-to-confirmation time | Hours from an order arriving to the customer receiving a confirmation. |
| Order entry error rate | Lines with the wrong item, quantity, price or address per 1,000 lines entered. |
| Touchless order rate | Share of orders created and confirmed with no manual correction. |
| Open deductions | Value and age of customer deductions not yet resolved. |
| Quote turnaround | Hours from a quote request to a sent, approved quote. |
What can go wrong in distribution, and the control for each.
A wrong order line in wholesale is expensive. It ships, it comes back and it costs freight both ways. These are the failures we design against first.
| Failure mode | Control | How we'd detect it |
|---|---|---|
| Wrong item mapped from a customer part number | Only confirmed cross-references are used automatically. A new or ambiguous mapping goes to a person once, then becomes a rule. | Returns tagged "wrong item" traced back to the mapping that created them. |
| Order entered at the wrong price | Prices come from the customer's contract in the ERP, never from the email text. Differences from the customer's stated price are held. | Daily report of price overrides and of invoices disputed for price. |
| Quantity misread (for example 10 cases read as 10 units) | Unit of measure is checked against the item master. Quantities far outside that customer's history are held. | Alert on orders above a set multiple of the customer's average. |
| Duplicate order | Deduplication on customer, PO number and lines before the order is released to the warehouse. | Alert on any two orders with the same customer PO number. |
| Quote below margin floor | Margin is checked per line and per quote. Anything below the floor needs a named approver. | Weekly review of approved exceptions against the floor. |
| Customer told a delivery date the business can't meet | Dates come only from stock, open POs and transport data. When the data is missing, the reply says so and a person follows up. | Late deliveries compared with the date promised. |
Order intake from email and PDF, from diagnostic to pilot.
Illustrative example — not a client result. The numbers below are assumptions chosen to show the method and the arithmetic. Your Audit replaces them with measured values.
| 01 | Diagnostic | Suppose a building-supplies distributor picks "order entry" on the E-commerce track. The Snapshot might show a High leverage signal with Medium confidence, friction at the Demand/Input and Processing stages, and Level 2 (workflow augmentation) as the indicated AI depth, because the ERP stays the system of record and the work is mostly reading and matching. |
| 02 | Audit | Suppose the Audit measures 2,400 non-EDI orders a month at 8 minutes each. That is 2,400 × 8 = 19,200 minutes, or 320 hours a month, about 2 FTE at 160 hours. It also finds that about 25% of orders have an unknown item, a price difference or a new delivery address, and need a person. |
| 03 | Pilot | Suppose the 75% clean orders go through as draft orders, with a person checking a 10% sample for 4 minutes each. The 25% exceptions take 10 minutes each because they are the harder cases. The Pilot measures whether that holds. |
| Line | Assumption | Hours per month |
|---|---|---|
| Baseline | 2,400 orders × 8 min | 320.0 |
| Clean orders, after | 1,800 orders, 180 sampled × 4 min | 12.0 |
| Exceptions, after | 600 orders × 10 min | 100.0 |
| After, total | 12.0 + 100.0 | 112.0 |
| Difference | 320.0 − 112.0 (about 1.3 FTE) | 208.0 |
At an assumed loaded cost of €42 an hour, 208 hours is about €8,740 a month. The Audit would also measure order entry errors and confirmation time, because fewer wrong lines means fewer returns and credit notes. It would also count the new costs: compute, ERP integration and exception review. If the numbers don't hold, the recommendation is "don't proceed".
Where our proof comes from.
We'll be plain about this. Our production proof is in AdTech, not wholesale. We have not yet run these distribution workflows for a client.
The architecture is the same one that runs in AdTech production: typed intake, deterministic checks before any action touches money or customers, bounded retries, then a person. Matching messy partner data to a clean record, and reconciling what was ordered with what was delivered and billed, is daily work in programmatic advertising. The case studies show that work, and five AI plugins built on this architecture are live at reviveadservermod.com.
Our engineering team and delivery network have built related systems: invoice and business document AI with layout-aware parsing, and an ERP/CRM assistant on self-hosted open-source models. See Selected builds.
That is why distribution engagements start with the free diagnostic and then the Audit. The Audit measures your own baseline first, so any decision rests on your numbers, not on ours.
Questions distributors ask first.
Most of our big customers already use EDI. Is there anything left to automate?
Often, yes. The long tail of smaller customers still sends emails and PDFs, and EDI orders still fail on unknown items, prices and addresses. The Audit counts both, so you can see where the time actually goes.
Do we need to change our ERP?
No. We work with the systems you have, through their APIs or import interfaces. The ERP stays the system of record, and agents create drafts that your rules release.
Will an agent decide a customer's credit limit or put an account on hold?
No. Credit decisions stay with your credit team. An agent can prepare the evidence, such as payment history and open deductions, but a person makes and records the decision.
Find out which order workflow is worth redesigning.
Start with the free diagnostic on the E-commerce track. Move to the Audit only if the Snapshot points to something worth measuring.
| 01 | Free AI Operational Diagnostic | 10 steps, 8–12 minutes, E-commerce / Marketplace track. Snapshot on screen and as a PDF. |
| 02 | Operational Leverage Audit, from $1,500 | Fixed fee, one workflow, 10–15 working days after data access. Measured baseline, benefit model with stated assumptions, go / no-go. |
| 03 | Pilot implementation, from $6,000 | Fixed scope. The workflow built and run in your environment, measured against the Audit baseline. Typically 4–8 weeks. |