AI-Powered Order Automation: From Manual Entry to Automated Process

For many sales teams, customer service, and back office, order entry is still today a sequence of copy-paste from emails, PDFs, and portals into the ERP system. This blocks scalability, increases error risk, and makes it difficult to guarantee fast SLAs to customers. In this article, we'll see how order automation really works, what "automated order import" means, and how an AI solution like TypeLens can transform the process without overhauling the existing ERP.

Why talk about order automation now

The order is the starting point of almost all core processes: invoicing, logistics, production, purchase planning. If the data here is slow or inaccurate, everything else suffers.

Typical problems we see in companies:

• Orders received via email, PDF, B2B portals, Excel, digitized fax.
• Manual entry into ERP/management system, often by customer service.
• Typing errors on item codes, quantities, prices, addresses.
• Double work: the salesperson enters the order in CRM or spreadsheet, the back office re-enters it in ERP.
• Difficulty handling peaks (seasonal, promotions, new large customer) without immediately increasing the team.

Automating this flow means ensuring that the order "enters" the company once, in the customer's format, and is intelligently brought where needed (ERP, CRM, planning systems) with minimal human touch.

What order automation and automatization mean

We talk about "order automation" or "order automatization" when:

• Order acquisition from sources (email, attachments, portals, shared folders) happens automatically
• Key data (customer, items, quantities, conditions) are extracted and structured
• The ERP system receives the order already filled, ready to confirm or validate with one click

In other words, it's not just "reading a PDF": it's orchestrating the entire flow from order arrival to its registration in the transactional system.

Essential elements

• Order document recognition (even if the format is not standard).
• AI data extraction, resistant to different layouts, languages, and small file changes.
• Normalization: mapping customer item codes to internal codes, associating correct price lists, applying business rules.
• Automatic creation or update of the order in ERP/management system, with checks and logs.

What automated order import is

"Automated order import" is the point where the customer's world (files, emails, portal) meets your ERP system.

This means:

• Orders are collected from dedicated inboxes, folders, or APIs without human intervention.
• Each order is interpreted by the AI engine (PDF, Excel, Word, image, etc.).
• Extracted data is transformed into the format required by your ERP (SAP, Zucchetti, TeamSystem, Odoo, etc.).
• The order is automatically created or updated via integrations/APIs, leaving the operator only final validation in case of doubts or anomalies.

From an operational perspective, the leap is simple but huge: moving from "every order is a manual activity" to "the operator intervenes only on deviations or exceptions".

Where orders come from and why AI makes the difference

Orders never arrive from a single source. A modern system must handle:

• Emails with attached orders (PDF, Excel, Word).
• B2B portals where the customer uploads a file or fills a form.
• EDI flows or structured formats.
• Even photos of printed orders or digitized faxes in some sectors.

Without AI, every layout variation requires creating or maintaining rigid templates: if the customer changes the PDF format or adds a column, the system "breaks".

With an AI engine trained on your domain, the algorithm learns to recognize:

• where the header is located
• how to identify order lines, item codes, descriptions, quantities, prices
• which elements are optional and which are critical

This allows managing dozens or hundreds of customers with different formats without having to create a "rule" for each one.

Practical example: from PDF in inbox to order in ERP

Imagine a typical flow with TypeLens or a similar platform:

1. Customer sends order via email with PDF attachment.
2. Email arrives in a dedicated mailbox monitored by the system.
3. AI engine analyzes the attachment, identifies the document as "customer order" and extracts data (customer, dates, addresses, lines with items/quantities/prices).
4. System maps any customer item codes to internal codes, applies price list policies, and flags any inconsistencies (e.g., unknown code, quantity out of range).
5. If everything is consistent, automatically sends data to the ERP, creating the order and setting it to the desired state (e.g., "To confirm").
6. Operator sees the order already ready in the system: can approve, modify a detail, or handle any exceptions.

The result: operators no longer spend their day typing order lines, but governing exceptions and adding value to the customer.

Concrete benefits for sales, customer service, and IT

Automating and automatizing order import is not just "doing things faster". The impacts touch multiple dimensions:

Time

Drastic reduction in hours dedicated to manual entry, with the ability to absorb peaks without immediately hiring new staff.

Data quality

Fewer copy-paste errors, more consistency between what the customer requested and what enters the ERP.

SLA and service

Faster order confirmations, less backlog, greater ability to respond to last-minute requests.

Scalability

The company can handle more volumes (new customers, new channels, more orders) without rethinking internal organization every time.

IT

Fewer one-off integration projects (file macros, custom scripts, manual imports), more centralized governance of the order process.

How to evaluate an order automation solution

If you're looking for a platform for automation and automated order import, some key questions to ask:

Document types

• Does it really handle PDFs, Excel, images, and mixed formats from your customers?
• Can it autonomously recognize different layouts without rigid templates?

ERP integration

• Are there ready-made connectors/APIs for your ERP or management system?
• Can you control the point where the order is created (state, approval flow, etc.)?

Adaptability

• Can you map customer codes to internal codes without endless custom developments?
• Does the system learn from operator feedback (e.g., repeated corrections)?

Governance and exceptions

• Is it clear what happens when an order is unreadable or missing data?
• Do you have a unified interface to manage exceptions, check logs, and monitor KPIs?

Security and compliance

• How is sensitive data and access logs managed?
• Do you have tools to demonstrate what happened to an order in case of disputes?

A solution like TypeLens is designed to cover these requirements: it brings artificial intelligence to the heart of the order process, without imposing an ERP change or architecture, and allowing the business to focus on time, quality, and customer service.

Where to start: an order automation pilot project

To start pragmatically:

1. Select 1–2 customers with significant volumes and "typical" formats.
2. Collect a set of historical orders (PDF, email, Excel) to use as training and test base.
3. Define 3–4 simple KPIs: average entry time, average number of lines per order, error percentage.
4. Start a pilot with an automated order import solution, maintaining a period of dual control (human + AI).
5. After a few weeks, compare before/after KPIs and decide how to scale to other customers/channels.

This way, order automation stops being an abstract concept and becomes a concrete, measurable project, with clear impacts on time, errors, and ability to give fast responses to customers.