Problem page

How to get enterprise AI pilots doing real work

Your company bought AI tools, ran a few pilots and saw good demos. Months later, nothing in daily operations has changed. The finance team still chases the same invoices by hand, the exceptions still live in inboxes and spreadsheets, and the people who know how to handle them are as busy as before. Leadership asks what the AI budget delivered, and the honest answer is a set of slides. The problem is rarely the model. It is everything around it: access to the right systems, permission to act, and someone who owns the outcome.

2 min readWritten from ferratalabs.aiWelcome page from Tablif · 23 Oct 2026
The short answer

Ferrata Labs builds custom AI agents that run inside your own environment. Their Brain platform connects to your ERP, such as SAP, NetSuite or Dynamics, and to the mailboxes and spreadsheets where exceptions are handled.

On this page
  1. Why the usual way fails
  2. How Ferrata Labs helps
  3. Step by step
  4. Tips
  5. Questions

01Why the usual way fails

Most pilots stop at the point where real work starts. The tool is not connected to the system of record, so it reads exports instead of live data, and nobody is willing to let it act on real transactions. The data is spread across the ERP, email and spreadsheets, while the judgment about what to do sits in people's heads and was never written down. Security teams are right to worry about sending company data to outside models. And without a clear owner inside the business, a pilot has no path into production.

02How Ferrata Labs helps

Ferrata Labs builds custom AI agents that run inside your own environment. Their Brain platform connects to your ERP, such as SAP, NetSuite or Dynamics, and to the mailboxes and spreadsheets where exceptions are handled. Two forward-deployed engineers work in your teams to build one workflow end to end. Every agent action goes through a human approval gate, and the agents and their logic stay yours after the engagement. The first goal is a single workflow running on real transactions, not another demo.

“You bought AI. Nothing does the work. The data sits in five places and the judgment sits in people's heads.”
From ferratalabs.ai
“One workflow, real transactions, live in under 90 days.”
From ferratalabs.ai

03Step by step

  1. Pick one workflow with real transactions and a clear owner, for example accounts receivable.
  2. Connect the Brain to the system of record and the mailboxes where the exceptions arrive.
  3. Have the engineers work in your standups and tickets to build the agent in your stack.
  4. Run the agent with an approval gate on every action until it earns more autonomy.
  5. Keep the agents and logic in house and use them as the base for the next workflow.

04Tips

  • Choose a boring, frequent workflow for the first agent. Collections, invoice matching or order exceptions happen every day, so you see results quickly and people trust the numbers.
  • Make the agent read live data, not exports. An agent that works from yesterday's spreadsheet will always need a person to check it.
  • Keep a person in the loop at first. Approval gates let the team see every decision the agent proposes before anything touches cash or customers.
  • Ask early who owns the result. A pilot that belongs to nobody inside the business rarely makes it to production, however good the model is.

05Questions

How long until the first agent is live?

Ferrata Labs says one workflow goes live on real transactions in under 90 days.

Source: ferratalabs.ai
Does my data leave our environment?

No. It runs in your cloud and network boundary, and nothing calls home for permission to run.

Source: ferratalabs.ai
Is there per-seat pricing after the project?

No. The agents are yours and there is no per-seat rent on your own operation.

Source: ferratalabs.ai

Build custom AI agents that execute work in manufacturing, financial services, and supply chain businesses.