Use cases

Real applications of agentic AI in operations, finance, and administration for mid-size companies.

Accounts Payable Automation: How to Build the ROI Case Before You Build Anything

Every vendor invoice moves through a manual chain: someone receives it, reviews it, codes it against the purchase order or relevant cost center, uploads it to the ERP, and routes it for approval. As invoice volume grows, this chain becomes the bottleneck of the accounts payable cycle, produces duplicate or late payments, and leaves little visibility into where each invoice is stuck. That lack of traceability also complicates internal and external audits: when a vendor claims a payment is overdue, reconstructing exactly where the invoice stalled can take hours of manual searching across email, the ERP, and the intermediate spreadsheets each team member keeps. The problem isn't only operational — it's also a decision problem. Before justifying the project internally, the CFO needs to answer the two objections that almost always surface first — budget and return — with data, not promises.

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Operations

AI Agent for Recurring Internal Requests: Fewer Interruptions to Your Administration Team

The administration team spends between 5 and 15 hours per week responding to internal requests that are, for the most part, repetitive and have a standard answer. Each interruption carries a context-switching cost. The team cannot prioritize higher-value work because the volume of inquiries does not stop.

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FinanceIntegration

Automated Bank Reconciliation: Month-End Close Without Manual Statement Matching

Month-end close is systematically delayed because bank reconciliation is still done manually: someone on the accounting team exports each statement, matches it against recorded entries, and notes discrepancies by hand — duplicate payments, amounts that don't match, transactions posted on a different date than recorded. The more bank accounts the company has, the more the workload grows, and the process usually depends on one person who knows the historical shortcuts and exceptions, creating a single point of failure when that person is out or changes roles. Many teams know this matching process could be automated but don't have anyone internally available to build and maintain it: in our real pipeline over the past 12 months, 'insufficient internal resources' comes up 13 times as the explicit reason for not moving forward with this type of automation, almost always framed as 'we know, but we don't have anyone to build it.'

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Finance

Board and Management Report Preparation Agent: From Data to Draft in Hours

Preparing the management report involves extracting data from multiple sources (ERP, CRM, spreadsheets), consolidating it, drafting the narrative analysis, and formatting the presentation. The process is manual, repetitive, and prone to version errors. The CFO or their team invests time in assembly work that does not require their judgment, yet cannot easily be delegated.

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Finance

Client and Project Profitability Agent: The Visibility Your ERP Doesn't Provide

The company knows its total revenue and aggregate costs, but cannot determine with precision which clients or projects are profitable and which consume resources beyond what is billed. Producing that analysis requires cross-referencing billing data, allocated hours, direct costs, and indirect costs — a task no one has the bandwidth to perform on a recurring basis. As a result, pricing and renewal decisions are made without real profitability data.

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Operations

Contract and Expiry Tracking Agent: No More Missed Renewals or Surprises

Contracts live in email folders, shared drives, or physical files. No one has centralized visibility into what expires when, which terms apply, or which contracts auto-renew under unfavorable conditions. The team typically learns about an expiry when it is already too late — or when the supplier sends a notification first.

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FinanceIntegration

Corporate Card Expense Reconciliation Agent: Expense Control Without Spreadsheets

The finance team spends 10–20 hours per month reviewing card statements, matching receipts and supporting documents, identifying unsupported transactions, and chasing employees to complete documentation. The process is reactive, concentrated at month-end close, and generates internal friction.

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ManufacturingIntegration

Real Case: Automated Quoting for a Custom Door Manufacturer (€2,500 Pilot)

This is a real, anonymized case from our pipeline: a Spanish manufacturer of custom-made doors, mid-size, running its operation on Velneo as its ERP. Every customer order requires a quote that combines specific measurements, materials, finishes, and pricing rules that vary by model — a process currently done by hand by one person, cross-referencing the order against price tables and product configuration inside the ERP. The more orders come in, the more this task becomes the bottleneck between customer interest and the commercial proposal: every day a quote takes to go out is a day the customer could be comparing with another supplier. This bottleneck isn't only internal: in a sector where several manufacturers compete for the same order, commercial response speed is itself a competitive advantage, and a quote that takes days to go out can cost the order even when the final product would be competitively priced.

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FinanceIntegration

Real-Time Visibility Into Purchasing Spend: The Question Every CFO Asks Before Close

The question sounds simple — how much has the company committed in spend this month — but the real answer is scattered across open purchase orders, vendor invoices not yet recorded, and corporate card charges that haven't reached the ERP yet. The CFO ends up rebuilding that picture by hand, cross-referencing reports from different systems, and by the time it's ready, it's already outdated. The consequence isn't just lost time: it's making spending decisions — approving or holding a purchase, adjusting a department's budget — with information that's weeks behind the reality of the business. Even knowing this is a problem AI can solve, many CFOs hesitate to move forward because human validation still weighs heavily on the final decision: in our real pipeline over the past 12 months, 'human validation is still necessary' comes up 12 times as an explicit objection when we propose this type of agent, and 'I'm too busy right now' another 8 times — both reflecting the same underlying concern: delegating spend visibility without losing control over the final call.

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OperationsIntegration

Vendor Onboarding Agent: Validation and Registration Without the Administrative Overhead

Registering a new vendor requires collecting documentation, verifying tax data, checking against risk lists, creating the record in the ERP, and notifying the requesting department. The process can take 3 to 10 business days, depends on multiple people remembering to complete their part, and produces frequent errors: incorrect tax data, incomplete documentation, duplicate records.

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