Documents scanned with a scanner next to a flowchart on monitor

Automation of business processes with AI

Automations to process documents, classify requests and transfer data, with checks defined by process.

AI-generated

We evaluate repetitive tasks such as extracting data from documents, organizing requests, and transferring information between tools.

Feasibility is verified on a limited case, defining expected results, human controls and exception management methods.

Paper documents, scanner and workflow on a laptop
AI-generated

Analyze the process before automating it

Orders received in PDF, emails to assign and documents to classify are examples of activities to evaluate. The quality of the result depends on the data, the variability of the cases and the planned controls.

We describe the source of the information, steps, responsibilities and destination of the results. The prototype allows us to evaluate whether to proceed with theAI integration in business tools.

Examples of automatable processes

Incoming documents

Orders, invoices, delivery notes and forms read automatically: the extracted data is checked and loaded into the management system.

Sorting of requests

Emails and forms classified by type and urgency, routed to the right person with a draft response ready.

Business knowledge

Manuals, sheets and procedures that can be consulted with questions in natural language, with the sources always indicated.

Switches between systems

Data transferred between e-commerce, CRM, business software and spreadsheets without manual copying.

Where to evaluate an automation

  • Frequent and repetitive activities that follow stable rules
  • Processes with data already available, even in different formats
  • Steps where a human control can catch exceptions
  • Offices that today copy information by hand between one system and another

On data: before development we define together which information is processed, by which services and with what guarantees, in compliance with the GDPR and your internal policies.

From the use case to the automation in operation

  1. Choice of caseWe identify a process with sufficient volume and an outcome that is easy to measure.
  2. PrototypeWe test automation on real data and measure quality and exceptions.
  3. IntegrationWe connect the flow to existing tools, with controls and operation log.
  4. ExpansionOnly after the measured results are the scope expanded to other cases.

Frequently asked questions

How reliable is data extraction from documents?

It depends on the quality and variety of documents. This is why we start from a prototype on real cases: we measure the percentage of correct data and provide human control on uncertain cases.

Do we need to replace our existing software?

Let's first evaluate the possibilities of integration with the tools already in use. If a system has limitations, we describe them in the analysis and propose available alternatives.

Who checks that the AI doesn't make mistakes?

The flow includes human verification points where an error would have consequences, and a log of each operation. The thresholds are decided together and reviewed with the data.

How much does it cost to maintain an automation?

We consider development, use of AI services and maintenance in relation to expected volumes. The estimate is compared with the expected benefits and verified through the prototype.

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Let’s discuss your project

Tell us about your business, your goals and the tools you use. We will assess your requirements, define the work involved and prepare a proposal.

info@labelstudio.it +39 0422 162 6069