AI brought the efficiency. Governance is still on us.
We use artificial intelligence at every stage of building software. And we believe it only pays off with method, human review and someone who answers for the result. This is our manifesto: what we believe, how we work and what we guarantee to the people who build with us.
Everyone is using AI. Few answer for what it delivers.
Companies are being pushed to use AI, and the shortest path is to bolt a tool on top of the same old process. Code ships faster, but nobody really knows where it came from, who reviewed it or whether it is safe.
In software that moves money, data or operations, that is not a gain. It is risk that shows up later, as failures, rework or an audit finding.
We chose another path: we redesigned the way we work with AI at the center, without giving up on who answers for each delivery.
Efficiency with governance. One without the other is no use.
Efficiency
Specialized AI agents work at every stage and take repetitive work out of the way.
- Legacy systems read and assessed with agent support
- Code, tests and documentation generated together
- Engineers focused on the decisions that matter
Governance
Rules agreed in writing and named people approving every step.
- Scope, security and regulatory limits defined before we start
- Human review and security testing before every delivery
- A trail for every change, ready for audit
Six convictions behind every project.
- 01
AI without rules creates problems faster.
Speed only helps when the path is right. Before a single line is generated, we agree in writing on what is allowed and what is not.
- 02
AI does not sign. A person does.
Every delivery is approved by someone on our team, by name. The machine suggests; people decide.
- 03
Specialists beat generalists.
We use AI agents built for specific tasks, such as analyzing code, testing and reviewing, not a generic assistant that tries to do everything.
- 04
Working software is worth more than a report.
We do not hand over an assessment for another vendor to execute. We go from assessment to a live system.
- 05
Experience is not thrown away. It is taught.
DB1's 26 years of hits and misses feed our tools. AI starts where we left off, not from scratch.
- 06
Speed without a trail is risk, not advantage.
You can see where every change came from, who approved it and why.
Five steps. A human sign-off in each one.
- You bring your business challenge.
- AI agents read the code and the business and map where the problem is.
- A person on our team validates the discovery.
- Agents document each part of the system.
- We review and sign the project rules, the Harness: what the AI can and cannot do.
- Agents turn the rules into a specification, a plan and tests.
- A person approves the plan before the first line of code.
- Agents write the code within the rules.
- Security tests run automatically on every delivery.
- An engineer reviews and approves every delivery.
- Release to production is automatic.
- Agents follow the running system.
- Every quarter, a person reviews the health of the system.
- what we learn feeds the next cycle
Before touching the code, we understand your business, its constraints and where the opportunity is.
We write down the scope, the security and regulatory limits and what "done" means. That document, the Harness, guides the AI for the whole project.
We turn the rules into a specification, a plan and tests, before the first line of code.
Our agents write code within those rules. Every delivery goes through engineer review and security testing before it moves on.
We monitor the running system. What we learn becomes an improvement in the next cycle.
Legacy modernization with 92% more efficiency
Legacy modernization with 92% more efficiency
The 92% is not a slide estimate. Our engineering team presented the method and the numbers on stage at APIX 2026.
Conviction without results is just opinion.
Efficiency
efficiency gain modernizing complex legacy code, compared with a manual rewrite.
Governance
right the first time: fewer than 3 bugs per 100 deliveries, because review happens during the project, not at the end.
Experience
building and modernizing critical software, part of DB1 Group.
Who has already built with us.
See all cases →
The way we work is open for anyone to read.
Engineering Guide
The DB1 way of building software, documented in three tracks: Engineering, QA and DevOps. It is what our teams follow and what our agents read.
Coverage, maintainability, duplication, reliability and security. Measured, not estimated.
Tech Radar
Our position on every technology we use in production. Nothing makes it onto the radar without going through a real client project.
Roberto Padilha
CTO · DB1 Itênex