AI agents don't come off the shelf. We build them with you, inside your operation.
Most agents stall between the demo and the operation. Itênex puts yours in production, integrated with your systems and measured, with your team learning along the way.
We don't sell slides about AI. We put agents in production and leave your team ready to run them.
Right the first time
of deliveries with no rework: fewer than 3 bugs per 100, because every cycle goes through human review.
From assessment to pilot
to go from "where do we start" to a validated, measured agent.
Experience
of critical software engineering behind the method and the tools.
The problem is rarely the model. It is what is missing around it.
An agent is not a chatbot: it queries your systems, decides and acts. When the foundation around it fails, it gets things wrong fast and at scale.
Messy data
An agent is only as good as the data it queries. With outdated spreadsheets and systems that don't talk to each other, it decides wrong, just faster.
Integration left for last
It is the most critical step and the most underestimated. Bolted on afterwards, with no access control or audit trail, it fails exactly when the agent needs to act.
Nobody checks if it is right
Without metrics agreed before go-live, the agent degrades quietly: the model changes, the data changes, the process changes, and nobody notices until a customer complains.
Only the vendor understands it
A vendor or a single person built it. When they leave, nobody knows how to change the agent, and it stops evolving.
See what level your company is at and what the next move is.
Five questions, about a minute, no sign-up. Your point lands on the map with each answer.
The five questions
- Do you already know where an AI agent would create the most value?
- Is there budget and people to build and maintain an agent?
- Could an agent query your data and systems today?
- Who drives the agent agenda at your company?
- How do you control what AI decides and does?
You on the map
Seeing where to apply AI is common. What falls behind is executing with method.
| Pillar | You | Average | Companies’ range |
|---|---|---|---|
| Market and customers | - | 47 | 43-53 |
| Resources and investment | - | 40 | 32-52 |
| Technology and infrastructure | - | 38 | 23-52 |
| Culture and leadership | - | 37 | 22-60 |
| Processes and governance | - | 35 | 17-51 |
A preview from one person’s answers, to help you get your bearings. The range shows 7 companies that completed a fuller AI maturity assessment: it is context, not a position. Points and cut-offs are DB1 Itênex’s choice. It is not a certification or a market ranking.
Want to understand how we think about AI maturity? Read the AI Maturity Guide
Four steps, one for each failure.
Discover
We start with the problem, not the technology: the process that eats the most time or the error that costs the most. We map the data and systems the agent will query and what needs fixing first.
Assessment in 2 weeksBuild together
Integration is built with the agent, with access control and an audit trail. A language model where text needs to be understood, fixed rules where the flow is rigid. Everything tested with real data before production.
Pilot in ~30 daysMeasure
Metrics are agreed before go-live: accuracy rate, response time and how many cases the agent hands to a person. In production, we track them and adjust when the model or the business changes.
Measured in productionHand over
Your team builds in pairs with ours and keeps the playbook and the written rules. Whenever you want, it takes over the agent and builds the next one on its own.
Team upskilled
What Itênex brings that an off-the-shelf tool doesn't.
The people who sell are the people who build
Applied AI engineers, assessed with a technical report, write the agent with your team. No hand-off to a junior team after the sale.
Our own tools
Clovis Agentic and Harness, which we use on our own projects: every agent follows written rules for scope, limits and acceptance criteria, and stops at every human approval.
Integration is our day-to-day
We come from engineering critical and legacy systems. Connecting the agent to the ERP, the CRM or an old system with no API is routine, not a project risk.
Certified governance
CMMI DEV/3, ISO/IEC 27001 and ISO/IEC 27701: access control, audit trail and personal data protection from day one.
No lock-in
Architecture, rules and playbook stay in your environment. We use the model that makes the most sense for the case, not a single vendor's.
Open method
Our agentic engineering method was presented at APIX 2026 and has a public Engineering Guide and Tech Radar. You see how the work is done before you hire us.
Before and after the agent.
Everything you need to know
What is the difference between an AI agent and a chatbot?
A chatbot follows a script of questions and answers. An agent reads the context, queries company data, decides and acts: it opens a ticket, fills in a record, writes to the ERP. That is why it needs integration and governance from the start.
Does every process need an agent?
No. It pays off when the task is repetitive, has volume, the data sits in a system that can be queried and the gain can be measured. If the process still changes every week or depends on judgment and negotiation, we say so, and start with what comes first.
What do our systems need before they can take an agent?
API access to the main systems, organized data, a test environment separate from production and access control with a record of who did what. If something is missing, it becomes the first step of the project.
Off-the-shelf agent or custom-built?
For a generic process, with the integration the vendor already supports, an off-the-shelf tool works, and we will tell you so. Custom makes sense when the process is specific to your operation, uses data only you have or needs deep integration with your systems.
We have an AI pilot that stalled. Can it be salvaged?
Almost always. We review the architecture, data and governance of what exists, find out why it didn't scale and define the path to production. You don't start over.
Will we depend on Itênex afterwards?
No. Your team builds alongside us, you own the architecture, the rules and the playbook, and you take over whenever you want. If you prefer, one of our squads keeps evolving the agents with you.