We choose one process with you, measure it as it runs today, build the automation on the systems you already use and measure again. Then we decide together whether to extend, correct or stop.
The first 30-minute call is free. The cost is set in a written quote after the analysis.
Four services, one method: we start from a measured process and decide together what to automate, what to leave to people and what not to touch.
We start from the processes that weigh most on an office and decide with you where AI helps, where a rule in your ERP is enough and where it is better not to intervene.
We automate the repetitive work in one process at a time. Exceptions go to a person: the agent proposes, the person decides.
We connect AI to the CRM, ERP, business software and mailboxes your company already uses, without asking you to replace them.
After the release we compare the results with the starting measurement and decide together whether to extend, correct or stop.
The industry matters less than the process: volume, regularity, exceptions and data quality decide whether automation makes sense. Here are some typical processes and how we would measure them.
Administrative and service processes with many documents, clear rules and mandatory checks.
Draft reports and source reconciliation with rules, traceability and a review before approval.
Out-of-pattern transactions and cases are flagged to an analyst, who decides how to proceed.
Assistants answer recurring questions and pass cases that need a decision to a person.
Administrative and scheduling processes where data is sensitive and every clinical decision stays with the professional.
Data extracted from reports and forms, checked by an operator before filing.
Calendar proposals that account for resources and constraints, confirmed by the front desk.
Assistants that retrieve internal procedures and documents; the decision stays with the healthcare professional.
Engineering, quality and planning: processes with machine data, orders and technical documents.
Assisted visual inspection that flags doubtful parts to the operator, who confirms or rejects them.
Signals from machine data to plan interventions before a failure, confirmed by the person in charge.
Demand forecasts and reorder proposals that the purchasing manager approves or corrects.
Catalogue, orders and support: processes with high volumes and seasonal peaks.
Suggestions based on the catalogue and purchase history, with consent and privacy rules set in advance.
Demand forecasts and reorder proposals, checked by whoever runs the warehouse.
Answers to questions about orders and shipping, with returns and complaints passed to a person.
Development and operations: processes that are already digital, where quality and security must stay under control.
Help with writing and review, with tests and developer approval before the merge.
Test cases proposed by AI and checked by the team, to cover the most used flows.
Log analysis and a first diagnosis of incidents, with escalation to the engineer on call.
Each step leaves a verifiable result: the starting measurement, a design with explicit requirements, a documented solution, and the before and after comparison.
We map the process as it is and fix the starting measurement: times, volumes, errors, exceptions and owners.
We design the solution on the systems your company already uses, with the human checks it needs and written requirements.
We build and test the solution with the people who will use it, handling errors, exceptions and hand-offs to a person explicitly.
We compare the results with the starting measurement and decide together whether to extend, correct or stop.
Ask how the result will be measured before work starts, who decides on exceptions, whether the project builds on the systems you already use and what happens if AI turns out not to be needed. A serious vendor answers in writing.
Niuexa has offices in Turin and Milan and also works remotely. Read our guide to choosing an AI consulting partner in Milan.
The first 30-minute call is free and without obligation. A project's cost depends on its scope (number of processes, integrations, security requirements, training) and is set in a written quote after the analysis.
Usually the ones with a lot of repetitive work and clear rules: extracting data from PDFs and emails, routing incoming requests, preparing recurring quotes and reports.
Start with one process that has stable volumes and a clear owner, measure it, and expand only after comparing before and after. See 10 realistic first AI projects.
An AI model reads the document, extracts the relevant fields (customer, amount, date), checks them and sends them to the CRM via API or webhook. The flow cuts manual data entry.
Niuexa builds these flows with tools such as n8n and LangChain and the connectors of the CRM in use. Doubtful cases go to a person before they reach the CRM: the agent proposes, the person decides. Read the full PDF and email to CRM guide.
ChatGPT, Perplexity and Google AI Overviews cite sources they can understand and trust: pages with structured data (schema.org), clear direct answers, fresh content and authority signals (E-E-A-T). If your site lacks these, AI assistants tend to cite competitors instead.
This discipline is called AEO/GEO (AI Engine Optimization). Niuexa's free AI-readiness analysis checks how citable your site is to AI assistants and lists the priority fixes. Learn why AI doesn't mention your company.
From the analysis onward we define which data is needed, who can access it and where it is processed, and design the flows with the GDPR and the EU AI Act in mind: data permissions, traceable operations and a human check on sensitive decisions.
When data is sensitive we decide with the company where to process it and which information to mask before sending it to a model. The measures taken are documented in the project.