The average distributor processes 60% of orders by hand — and pays for every minute of it.
See the math →

Auto-Orders

(Manual Order Entry Automation)

From any format to a verified ERP order — in minutes.

SETVI ingests every order — PO PDF, email, Excel, image, EDI, even voicemail — maps every line to your catalog, validates pricing, terms, and stock against your ERP, and writes a clean order back. Customers keep ordering their way. Reps stop typing. Exceptions only — never every order.
Book a demoSee how it works →
Minutes, not hours · <1% exception rate · 24/7 processing
Today's Inbox · Order Operations
live
247 orders today
$1.42M processed
2 exceptions
PDF
Acme Foodservice Co.
PO-78421 · 24 lines
24/24
Submitted
EDI
Riverside Memorial
850 · 32 lines
32/32
Submitted
EML
Beacon Hospitality Group
free-form email · 19 lines
18/19
Submitted
XLS
Cedar Hill Manor
attachment · 14 lines
14/14
Submitted
IMG
Eastside Provisions
handwritten · 8 lines
8/8
Submitted
5 of 247 shown · 2 need review
Open inbox
Why now

Order entry is the last great manual workflow in distribution.

Every distributor knows the cost. Reps and order-entry staff spend hours each day re-keying orders that already exist in an inbox, an attachment, or a voicemail. Three forces converging right now make every quarter of waiting more expensive than the last.

01

Customers won't standardize. And they won't have to.

Every customer sends orders the way that works for them — PDF, email, Excel, scan, voicemail, the same EDI-850 they've used since 2003. EDI was supposed to fix this 30 years ago. It didn't. The long tail of customers will never adopt a structured format, and they're a meaningful share of order traffic and revenue.

02

Volume is up. Headcount can't follow.

Every customer sends orders the way that works for them — PDF, email, Excel, scan, voicemail, the same EDI-850 they've used since 2003. EDI was supposed to fix this 30 years ago. It didn't. The long tail of customers will never adopt a structured format, and they're a meaningful share of order traffic and revenue.

03

OCR was a half-measure. Context is the whole job.

Every customer sends orders the way that works for them — PDF, email, Excel, scan, voicemail, the same EDI-850 they've used since 2003. EDI was supposed to fix this 30 years ago. It didn't. The long tail of customers will never adopt a structured format, and they're a meaningful share of order traffic and revenue.

Where your orders actually come from

Your EDI handles the top accounts. Your eCommerce handles digital-native buyers. The slice in the middle is what costs you.

~30%
EDI
Top 20-50 customers · already automated
~30%
eCommerce
Customer portal · self-service buyers
~40%
Manual entry
Email, PDF, phone, voicemail, scan, fax — what your CSRs type by hand
Auto Orders attacks the manual 40% — without disrupting your EDI program or your eCommerce.
The cost of waiting

Three places manual order entry costs you. Auto Orders closes all of them.

Hours your CSRs burn keying orders that already exist somewhere. Volume your team can't absorb without scaling headcount. Same-day fulfillment that sits in a queue because manual processing can't keep up. Together — that's the gap Auto Orders closes, every month.

Labor Savings
Capacity Recovered
Speed-to-ERP
Combined ROI
Distributor revenue
Manual orders/mo
Monthly cost
Annual cost
$50M
~1,700
$13K
$150K
$100M
~3,300
$25K
$300K
$200M
~6,700
$50K
$600K
$250M
~8,300
$63K
$750K
$500M
~16,700
$125K
$1.5M
$1B
~33,300
$250K
$3M
Distributor revenue
Manual hrs/mo today
CSR-FTEs freed
Headroom for growth
$50M
~340
~1.7 FTE
+30% volume
$100M
~680
~3.4 FTE
+35% volume
$200M
~1,350
~6.8 FTE
+40% volume
$250M
~1,700
~8.5 FTE
+40% volume
$500M
~3,400
~17 FTE
+45% volume
$1B
~6,800
~34 FTE
+50% volume
Order type
Manual time
Auto Orders
Improvement
Standard PO (10-15 lines)
8–12 min
~90 sec
~90% faster
Complex PO (30+ lines)
15–25 min
~2 min
~90% faster
EDI-850 (auto-validated)
3–5 min
~10 sec
~95% faster
Scanned / handwritten PO
10–20 min
~2 min
~90% faster
Voicemail order
5–15 min
~90 sec
~90% faster
Email order (free-form)
10–18 min
~2 min
~90% faster
Distributor revenue
Labor savings
Total annual value
Typical payback
$50M
$150K
$300–450K
~6 months
$100M
$300K
$600K–900K
~5 months
$200M
$600K
$1.2M–1.8M
~5 months
$250M
$750K
$1.5M–2.25M
~4–5 months
$500M
$1.5M
$3M–4.5M
~4 months
$1B
$3M
$6M–9M
~4 months

Labor savings. Manual order share calibrated at ~40% — the conservative case for distributors with mature EDI and eCommerce programs already in place. Industry data places the average closer to 50–60%, with smaller and less digital operations often at 70%+ manual. Per-order labor anchored at $7.50 (~12 minutes at a $37.50/hr fully loaded wage) — sitting at the low end of the $7–30 range cited across distribution operations studies. The upper end includes error rework and correction cycles, which we exclude here. Order volumes assume ~$1,000 average order value (varies by vertical — foodservice and jan-san run lower; industrial and electrical higher). Capacity recovered. Hours model: ~12 minutes per manual PO × monthly manual order volume = total CSR hours currently consumed by order entry. ~80% of those hours are redirected to higher-value work (exception handling, customer relationships, account growth); the remaining 20% covers exception review on orders that genuinely need a person. CSR-FTE conversion at 2,000 productive hours/year per CSR. Headroom for growth scales with team size and order-mix complexity. Speed-to-ERP. Manual processing time per order type calibrated to typical mid-market distributor benchmarks — open, customer lookup, line-item keying, UOM/price validation, save, acknowledge. Auto Orders time measured from inbound capture to ERP submit (validation pass included). Steady-state performance reflects post-ramp results after the typical 8–12 week customer-training window. Sub-2-minute submit is what makes same-day fulfillment achievable for orders that previously sat in a queue until end-of-day. Combined ROI. Total annual value = labor savings reclaimed + downstream recovery (2–3× labor, capturing rework, returns, credit memos, and customer-service reduction). Payback period reflects total annual value vs. Auto Orders licensing, calibrated to distributor revenue band. Licensing terms vary based on order volume and integration scope — your AE will model your specific case. References available under NDA.

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Why your stack hasn't fixed this

EDI got your top accounts. eCommerce got the digital-native ones. Everything else still flows through someone's keyboard.

Distributors have spent thirty years investing in tools to digitize order entry. Each one covers a piece. Together they leave the manual ~40% — and that gap is where Auto Orders lives.

Your EDI

Works for your top 20 customers. Doesn't help with the other 800.

EDI is fast and clean — when both sides have invested in mapping, validation, and a structured format. The reality is that most customers will never adopt EDI; the smaller and mid-tier accounts that make up the long tail are precisely the ones least likely to standardize. EDI handles the easy 20-30% of orders by count and leaves the rest — often the majority of order traffic, even when not the majority of revenue — to be typed by hand.
Your eCommerce

Self-service buyers love it. Most buyers aren't self-service.

Your portal works perfectly — for the customers who want to log in, browse, and check out themselves. The reality is most B2B buyers aren't self-service: they're procurement teams under deadline, restaurant managers calling at 11pm, healthcare buyers with negotiated contracts that don't fit a portal flow. They send a PO, not a login. Your eCommerce platform serves the buyers who came to it. It can't reach the ones who didn't.
Your OCR

Reads the characters. Misses the order.

Standalone OCR turns a PDF into text. That's it. It doesn't know that your customer's part number "BG-12X" maps to your SKU 88341. It doesn't know that "case of 24" needs to become 1 EA, not 24 EA, in your ERP. It can't validate pricing against the contract. Reps still touch every order — they're just touching it in a slightly nicer interface. The output isn't an order. It's a draft.
Your reps

The bottleneck you can't hire your way out of.

Order-entry teams are the cap on how much volume a distributor can run — a 30% increase in orders means a 30% increase in headcount, and tenured CSRs are increasingly hard to find and replace. Errors at this stage propagate everywhere: wrong SKU shipped, wrong price billed, returns, credit memos, customer-service backlog. And the institutional knowledge — which customer rounds up, which one always means EA when they write CASE — walks out the door at retirement.

Auto Orders is the layer your stack is missing — any format in, validated order out — sitting on top of the systems you already run.

What the numbers look like

Touch only what needs a human.

Auto Orders isn't measured in orders processed — that's just the volume. The real measure is what shifts: from rep hours typing to rep hours selling, from errors caught at fulfillment to errors caught upstream, from a backlog at 5 PM to a clean queue.

60%+

faster than manual order entry methods

<1%

exception rate — only orders that truly need a person

24/7

order processing — inbox never sleeps, backlog never builds

$4–6 mo

typical payback period — labor savings alone
Discover yours — week 1 of discovery

Send us a sample of your transaction data. Get your own number for your own book.

The same view, ranked against your own customer base with peer fit scores in your verticals. Yours to keep regardless of whether you proceed. Most distributors find their actual number is bigger than their sales leadership thinks.
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📎 Email the business case to your CFO
AO

Errors caught upstream, not at fulfillment

Pricing mismatches, ship-to defaults, stock issues, terms violations — flagged the moment the order is parsed, against your live ERP. The fulfillment team stops being the QA team for order entry. Returns, credit memos, and customer-service inquiries drop measurably from week one.

The exception flywheel

Every rep correction trains the system. Customer X's odd part-number convention is learned the first time a rep fixes it. Next time the same convention shows up in a PO from that customer, it auto-resolves. Six months in, the exception rate is materially lower than week one.
Performance figures (60%+ speed improvement, <1% exception rate, 24/7 processing, 4–6 month payback) reflect operational benchmarks observed in SETVI Auto Orders deployments across distribution verticals. Speed comparison is against typical fully-manual order entry workflows; exception rate is measured as orders requiring human review on first pass after the model has been customer-trained for a typical 8–12 week ramp. Payback is total annual value (labor + downstream recovery) vs. Auto Orders licensing. Customer-specific results vary based on PO format diversity, ERP complexity, and integration depth. References available under NDA.
From the field — anonymized customer voices

"I used to come in at 7am to type the overnight orders. Now they're already in the ERP when I open my laptop."

CSR Lead
$200M foodservice distributor

"We absorbed 30% more order volume from an acquisition without hiring a single CSR. The first month after go-live, the team felt the difference."

VP of Operations
$400M industrial supply distributor

"Exception rate sat at 25% in week one. By month three it was under 2%. The system learned our customers faster than I expected."

Director, Sales Operations
$150M jan-san distributor
How Auto Orders works

Four stages, one continuous pipeline. Customers don't change a thing.

Capture → Match → Validate → Submit. Every rep correction feeds back into the model — sharper matching next week, sharper still next month. The deep-dive below explains the Contextual Intelligence Engine that powers all four.

01

Capture

Orders arrive by email, PO PDF, Excel, image, EDI, or voicemail — Auto Orders ingests them all. Attachments, embedded tables, and free-form text all parsed. No customer behavior change required — they keep ordering their way.

Email · PDF · Excel · image · EDI · voicemail
02

Match

AI maps every line to your catalog with confidence scoring and cross-reference logic. Customer part numbers, manufacturer codes, free-text descriptions all resolved to your SKUs. UOM and pack-size conversion automatic.

SKU mapping · cross-reference · UOM · confidence score
03

Validate

Pricing, terms, ship-to, stock availability, and customer-specific rules checked against your ERP in real time. Live PO/contract pricing match. Credit limits and payment terms verified. Errors caught upstream, not at fulfillment.

Pricing · stock · terms · ship-to · credit · live ERP check
04

Submit

Clean order written directly to your ERP. Auto-acknowledgment sent to customer. Exceptions routed to a rep with one-click resolution and full context — every correction captured to train the system for next time.

ERP write-back · auto-ack · exception routing · audit trail

Behind the pipeline — the Contextual Intelligence Engine

Layer 01

Product Intelligence

AI research agents map customer part numbers, manufacturer codes, and free-text descriptions to your SKUs — with cross-reference accuracy across millions of products. The hardest line on the PO ("BG case 24, lemon scent") becomes the exact SKU in your catalog. Not a guess. A defensible match with a confidence score and reasoning shown.

Layer 02

Domain Knowledge

Industry-specific UOM conversions, pack-size rules, abbreviations, and substitution logic baked in. Foodservice, jan-san, electrical, industrial — each vertical understood out of the box. Domain context is what turns a string of text into an order line that actually fits how your business runs.

Layer 03

Customer Knowledge

Each customer's PO format, ship-to defaults, payment terms, blanket-order rules, and historical preferences are remembered — and applied to every future order automatically. Rep corrections become institutional knowledge. The system gets to know your customers as well as your most tenured CSR — and then keeps learning after they retire.

Self-improving
From PO to ERP — concrete example

An email arrives from Beacon Hospitality with an attached PDF. The PDF has 19 line items, free-form descriptions, and a part-number convention specific to Beacon's procurement system. Within seconds: 18 of 19 lines auto-matched against your catalog with 95%+ confidence. Pricing validated against Beacon's contract. Ship-to pulled from Beacon's defaults. One line — a discontinued SKU — flagged with a substitution suggestion. Order written to your ERP. Auto-acknowledgment back to the buyer. Total elapsed time: under two minutes. Total rep time: ten seconds to approve the substitution.

Capabilities

Every part of the pipeline. One order workflow.

Built for distributors and the systems they already run — from intake to validation to ERP write-back to acknowledgment.

Capture & Match

Multi-Channel Order Capture

Accept orders however your customers send them. Email, PO PDF, Excel, image, EDI, and voicemail intake. Attachments, embedded tables, and free-form text all parsed. No customer behavior change required.

Reps Stop chasing orders across inboxes — Auto Orders sees them all.
Admins Single intake pipeline replaces email triage and manual queues.

Intelligent Line-Item Matching

Powered by the Contextual Intelligence Engine. Customer part numbers, manufacturer codes, and descriptions all resolved to your SKUs. UOM and pack-size conversion automatic; substitution suggestions for OOS or discontinued items. Confidence score and reasoning shown for every match.

Reps Every line-item match is auditable and defensible.
AdminsConsistent matching logic across the entire team.
Validation & Review

Real-Time Validation

Every order checked before it hits your ERP. Live pricing validation catches PO/contract mismatches automatically. Stock availability and lead-time checks. Customer-specific rules: credit limits, ship-to defaults, payment terms — all verified upstream.

Reps No more bad orders entered, then chased and corrected.
Admins Errors caught upstream, not at fulfillment.

Exception-Based Review

Manage by exception — not by data entry. Clean orders flow straight through to ERP. Only flagged exceptions reach a rep, with full context and one-click resolution. Every rep correction trains the system for next time.

Reps Touch only the orders that actually need a human.
Managers Scale order volume without scaling headcount.
Integration & Learning

ERP Write-Back

Connect any ERP — orders land where they need to be. Modern middleware connects to SAP, Dynamics, NetSuite, DDI, Epicor, and more. Real-time API or scheduled batch — plus auto-acknowledgments to customers. Full audit trail for every order, every edit, every exception.

Reps No double entry — orders land in your ERP automatically.
Admins ERP becomes the single source of truth, kept clean by design.

Customer Learning

Smarter with every order processed. Each customer's PO format, defaults, and quirks learned over time. Recurring SKUs, blanket-order rules, and seasonal patterns recognized. Rep corrections captured as institutional knowledge — not lost when CSRs retire.

Reps The system gets to know your customers as well as you do.
Managers Prove ROI to leadership with hard numbers.
Output & Visibility

Order Acknowledgments & Confirmation

Customers always know where their order stands. Auto-generated acknowledgments sent the moment an order is written. Personalized confirmation — ship dates, pricing, and substitutions called out. Reduces inbound "where's my order" inquiries by default.

Reps Stop typing the same confirmation 50 times a day.
Admins Customer service load drops measurably from week one.

ROI & Operations Dashboard

Real-time visibility — hours saved, errors avoided. Live view of orders captured, validated, submitted, and exception-flagged. Per-rep, per-customer, per-channel volume and accuracy. Revenue at risk caught by validation: pricing, stock, terms.

Admins Tune confidence thresholds and rules with real data.
Managers Prove ROI to leadership with hard numbers.
Channels everywhere

Every channel your customers actually use.

Five intake surfaces. One engine. Each one tuned to the format it lives in — and all of them landing in the same clean ERP order.

Email + attachments
Inbox Capture

Monitored mailbox parses inbound POs in seconds. PDFs, Excel, embedded tables, free-form text — all extracted and matched. Nothing for the customer to learn.

EDI gateway
Structured Orders

EDI-850 and partner-specific formats handled natively for the customers who use them. Same downstream validation pipeline — same clean ERP write-back.

Image + scan
Vision Capture

Scanned PDFs, photos of paper POs, even handwritten notes parsed by vision-capable AI. The half of orders that OCR couldn't handle, handled.

Voicemail + phone
Voice Intake

Voicemail orders transcribed and parsed into the same pipeline. The customers who still call get the same clean order on the other end.

ERP write-back
Clean Submit

Orders land in SAP, Dynamics, NetSuite, Epicor, DDI — real-time API or scheduled batch. Audit trail complete. Auto-acknowledgment sent.

Use cases

Eight ways teams use Auto Orders every day.

Where eliminating manual order entry is the difference between scaling volume and capping it.

01 / 08
Operations efficiency

Process complex POs in dozens of customer formats — without templates.

Customer-specific PO templates were always going to be a losing battle: every customer changes their format eventually, new customers arrive faster than templates can be built. Auto Orders learns each customer's format from their actual POs — no templates to build, no templates to maintain.

Typical signal: 200+ active customers · each with a slightly different PO layout · template-maintenance debt eliminated · new customers onboarded by sending their first PO
02 / 08
Operations efficiency

Eliminate rekeying for high-volume customers without an EDI program.

High-volume customers who won't or can't do EDI are the most painful to support — large enough to demand fast turnaround, traditional enough to send PDFs. Auto Orders gives them EDI-grade speed on the format they already use.

Typical signal: top-100 account · sends a daily PO PDF · 40-line typical order · auto-processed in under two minutes vs. 15–20 minutes hand-keyed
03 / 08
Operations efficiency

Catch pricing and terms mismatches before fulfillment, not after.

A wrong price caught at fulfillment is a return, a credit memo, and a customer service inquiry. The same wrong price caught at intake is a one-line fix. Real-time ERP validation moves the catch upstream where it costs nothing to fix.

Typical signal: customer PO at $4.18/case · contract price is $4.32/case · flagged before submit · rep approves correction in three seconds
04 / 08
Operations efficiency

Replace standalone OCR plus manual review with one integrated workflow.

OCR + rep validation is two steps that don't talk to each other. The OCR drafts; the rep then validates every line, every match, every price — touching the order all over again. Auto Orders is one pass: extraction, matching, and validation in a single context-aware flow, with a rep only when something genuinely needs them.

Typical signal: OCR tool retired · rep time spent in the OCR's review UI redirected to exception handling · single audit trail across the whole flow
05 / 08
Operations efficiency

Handle voicemail and image POs without a person on the other end.

The "long tail" of order channels — voicemail, photos of paper POs, scans — usually means a CSR transcribing by ear or by eye. Auto Orders ingests them through the same pipeline as everything else, and the customer never has to change.

Typical signal: standing weekly voicemail order from a long-tenured customer · transcribed, matched, and submitted before the CSR opens their inbox · same accuracy as a structured PO
06 / 08
Internal operations

Scale order volume without scaling headcount.

Manual order entry forces a linear relationship between volume and headcount — a real cap on how much business a distributor can handle. Exception-based review breaks that line: a 20% increase in order volume now means a 1–2% increase in rep workload, not 20%.

Typical signal: M&A or organic growth bringing 30% more order volume · existing order-entry team handles it without new hires · rep time redirected to higher-value work
07 / 08
Internal operations

Cut "where's my order" calls with auto-acknowledgments.

A meaningful share of inbound customer-service calls are status checks on orders the customer assumed didn't go through. Auto-generated acknowledgments — sent the moment the order is written, with ship dates, pricing, and substitutions called out — close that loop by default.

Typical signal: CS team's inbound volume drops measurably in week one · "did you get my PO" calls largely disappear · CSRs redirected to genuine support
08 / 08
Internal operations

Prove ROI on order-processing transformation to leadership.

"How much does manual order entry cost us, really?" used to be answered with intuition. The Operations Dashboard replaces the gut estimate with hard numbers — hours saved, errors avoided, revenue at risk caught — defensible all the way up to the board.

Typical use: CFO/COO operations review · per-channel volume and accuracy · attributed labor savings · pricing discrepancies caught before fulfillment
ERP integrations

Connects to any major ERP. Without disrupting your workflows.

SETVI uses a modern middleware layer that connects to most ERPs — integration is fast and flexible regardless of your tech stack. We support real-time API connections, scheduled batch imports, or a hybrid of both. Weeks 1–2: SETVI works directly with your IT to map data sources and write-back rules. Weeks 3–4: capture pipelines deployed across email, EDI, and your other intake channels. Weeks 5–6: customer-specific learning calibrated; exception-handling workflow live with your reps. Typical go-live: 4–6 weeks, without disrupting existing customer ordering flows.

SAP
API
Microsoft Dynamics
API
NetSuite
API
Epicor / DDI
API / Import
+ More:
Acumatica · Infor · Sage · and leading wholesale ERPs — visit setvi.com for the full list
Security & compliance

Enterprise-grade. Always.

Role-based access controls with SSO across the platform
Encryption at rest and in transit
Full customer data isolation — your data never commingles
Complete audit trail for every action
SOC 2 Type II audit currently in progress
10+ years of enterprise data security operations
Regular penetration testing and vulnerability assessments
Common questions

Common questions buyers have.

What if our customers send POs in dozens of different formats?

That's exactly the problem Auto Orders solves. The system learns each customer's PO format — layout, part-number conventions, abbreviations, ship-to defaults — and applies that knowledge automatically. No customer-specific templates required. New customers onboard by sending their first order.

Do we need to change our ERP or customer ordering process?

No. Auto Orders sits alongside your existing systems and meets customers where they are. They keep sending POs the way they always have. Orders flow into your existing ERP through standard API or batch integration. Implementation is typically 4–6 weeks, without disrupting any existing customer workflows.

What happens when an order has a problem the system can't resolve?

It's routed to a rep as an exception, with full context: the original PO, the partial match the system attempted, the reason it was flagged (low-confidence match, missing SKU, pricing mismatch, credit issue), and a one-click resolution path. The rep's correction is captured and used to train the system, so the same exception is much less likely next time.

What about handwritten or low-quality scanned POs?

Vision-capable AI handles handwritten notes and low-quality scans far better than legacy OCR — and crucially, it brings context. A scanned PO with a smudged part number isn't a hard fail; the system uses the surrounding description, the customer's history with that SKU, and your catalog to make a confident match. Anything genuinely unreadable is routed as an exception with the original image attached for a rep to handle.

How is this different from EDI or our existing OCR tool?

EDI requires every customer to adopt a structured format — most won't. OCR pulls text but doesn't understand context, so reps still validate every line. Auto Orders handles any format customers actually send, learns each customer's patterns, and validates against your ERP before write-back. EDI handles your top customers; Auto Orders handles the long tail. OCR makes a draft; Auto Orders makes a submitted order.

How accurate is line-item matching?

Out of the box, the system delivers strong first-pass match rates by combining customer cross-references, manufacturer codes, your catalog metadata, and domain-specific abbreviation logic. Every match carries a confidence score and reasoning shown in the UI — defendable, not a black box. The exception rate drops materially over the first 8–12 weeks as the system learns each customer's individual conventions through rep corrections.

How long does implementation take?

Typical go-live is 4–6 weeks. Weeks 1–2: data and ERP integration mapping with your IT team. Weeks 3–4: intake pipelines deployed across email, EDI, and other channels. Weeks 5–6: customer-specific learning calibrated; exception workflow live with reps. Customer accuracy improves materially over the first 8–12 weeks of live operation as the system learns from real PO traffic.

How is our data protected?

Fully isolated, encrypted at rest and in transit. Role-based access controls and complete audit trail on every order, every match, every exception. SOC 2 Type II audit currently in progress. 10+ years of enterprise data security operations behind the platform.

See your own orders flow.

Bring us a sample of your real customer POs — the messy ones. We'll show you exactly what flows through, what gets flagged, and what your team gets back.
Book a demo