CSRs spending 15–20 minutes per order manually entering PO data into the ERP
Services
AI & Machine Learning · Document Intelligence
Stop paying people to type numbers from one system into another.
Manufacturers still process thousands of POs, invoices, RFQs, spec sheets, and BOLs manually — reading PDFs, retyping data into the ERP, and fixing the errors that come with it. Document intelligence extracts structured data from unstructured documents automatically, with validation rules that catch errors before they enter your systems.
4fit signals
6scope modules
5delivery stages
Intelligence layeroperating layer
01
The Problem
Manual Data Entry That Shouldn't Still Exist
Extract data from POs, invoices, RFQs, spec sheets, and BOLs automatically using NLP and document AI. Eliminate manual data entry from paper and PDF-based manufacturing workflows.
AP teams rekeying invoice data from PDFs and paper — introducing errors on 5–10% of transactions
RFQ responses delayed because someone has to manually pull specs from drawings and data sheets
No structured data from incoming documents — everything lives in email attachments and shared drives
02
Scope
What this service has to produce.
The work is organized as modules because implementation scope should be visible before the build starts.
01
Purchase Order Extraction
Automatically extract line items, quantities, pricing, ship-to addresses, and terms from incoming POs in any format — PDF, email, fax image, EDI. Validate against your item master and pricing rules before entry.
02
Invoice Processing
Extract vendor, line items, amounts, PO references, and payment terms from supplier invoices. Three-way match against PO and receipt automatically. Route exceptions for review instead of manually matching every invoice.
03
RFQ & Spec Sheet Parsing
Extract technical requirements, material specifications, quantities, and tolerances from RFQs and engineering drawings. Structure the data so your estimating team starts with a populated template instead of a blank screen.
04
BOL & Shipping Document Processing
Extract shipment data from bills of lading, packing slips, and carrier documents. Automatically reconcile against expected shipments and flag discrepancies.
05
Multi-Format & Multi-Language
Handle PDFs, scanned images, email bodies, Excel attachments, and handwritten forms. Support for multi-language documents common in international supply chains.
06
ERP Auto-Entry with Validation
Extracted data flows into your ERP with configurable validation rules — item number verification, price tolerance checks, quantity limits, and customer account validation. Errors are caught before entry, not after.
03
Architecture
The service has to fit the operating layer it touches.
Intelligence layerWhich decisions can be automated, which need review, and which should stay human-owned.
Governance dependencyThe agent needs governed inputs, clear action boundaries, and audit logging before it can touch production workflows.
Data the model must trust
ERP history
exception queues
pricing rules
quality records
fulfillment events
What we check before implementation
- Which system owns the record of truth.
- Where manual work or reconciliation enters the workflow.
- Which integrations, rules, or data cleanup have to come first.
04
Delivery sequence
How the work moves from diagnosis to production.
Manufacturers still process thousands of POs, invoices, RFQs, spec sheets, and BOLs manually — reading PDFs, retyping data into the ERP, and fixing the errors that come with it..
01
Document Workflow Audit
Inventory all document types processed manually — POs, invoices, RFQs, BOLs, spec sheets. Quantify volume, error rates, processing time, and cost per document. Prioritize by ROI.
02
Template & Model Training
Configure extraction templates for your most common document formats and train models on your specific document variations. Each supplier and customer may format documents differently — the model handles it.
03
Validation Rules & Business Logic
Define the validation rules that catch errors before data enters your ERP — item master lookup, price tolerance, quantity checks, customer/vendor verification, and duplicate detection.
04
ERP Integration & Routing
Connect extraction outputs to your ERP's order entry, AP, or purchasing modules. Configure exception routing for low-confidence extractions or validation failures.
05
Production & Accuracy Improvement
Deploy with accuracy tracking, exception dashboards, and continuous model updates. Extraction accuracy improves as the model processes more of your specific document formats.
05
FAQ
Questions that usually decide the scope.
These answers help separate a real implementation plan from a generic technology discussion.
PDF (native and scanned), email bodies, Excel/CSV attachments, TIFF/JPG images (including fax), Word documents, and EDI. If your team currently reads it and types data from it, we can automate the extraction.
Next step
Start with the operating problem, then sequence the build.
Metrotechs maps the record, traces the workflow, identifies the leakage, and turns the scope into a practical plan for Odoo, AWS, data, automation, portals, and AI.
Built around real records, workflows, governance, and production handoffs.
Scoped to what can be implemented, owned, and operated after launch.