AI Transformation

AI Reliability & Economics

Put AI into production knowing how much it costs and where the risks lie.

As AI enters processes and products, the need to understand what happens after it starts operating also grows.

AI Reliability & Economics creates mechanisms to track the quality, cost, and risk of AI in production. We define criteria, instrument the operation, and create evaluation and improvement cycles so that the company has control over systems that change with each interaction.

%

of executives lack confidence that their organizations would be prepared for an AI governance audit within the next 90 days.

(Grant Thornton, AI Impact Survey, 2026)

%

of the surveyed workers use personal AI tools for professional activities.

(MIT NANDA, State of AI in Business, 2025)

Governance starts with what we can observe

We define what it means to work well

We establish quality criteria, acceptable limits, and indicators to evaluate the behavior of the solution in production.

We define what it means to work well

We establish quality criteria, acceptable limits, and indicators to evaluate the behavior of the solution in production.

We continuously evaluate

We structure evaluations and tests to identify regressions and behavioral changes before they become major problems.

We continuously evaluate

We structure evaluations and tests to identify regressions and behavioral changes before they become major problems.

We create visibility into the operation

We instrument solutions to monitor quality, usage, cost, and failures to make deviations identifiable.

We create visibility into the operation

We instrument solutions to monitor quality, usage, cost, and failures to make deviations identifiable.

We govern access and risk

We define traceability and security criteria so that the company can understand and be accountable for what its systems do.

We govern access and risk

We define traceability and security criteria so that the company can understand and be accountable for what its systems do.

In critical and highly regulated markets, reliability must be built into the solution from the very beginning.

TRINCA has been structuring mechanisms to get critical systems ready to scale AI responsibly.

For a global insurer, we created mechanisms for traceability and failure detection and recovery across systems, with security, governance, and privacy-by-design criteria. In parallel, the underwriting journey now features a digital capability that consolidates data and knowledge, applies automated risk rules, and keeps the final decision with the specialist.

You can
find us at

PORTO ALEGRE (HQ)

1761 Paraná Ave

4th District,

Brazil

BARCELONA

Norrsken House

Passeig del Mare Nostrum,

15 Ciutat Vella,

Spain

MIAMI

TRINCA US

777 Brickell Ave #521

Miami, FL 33131

USA

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Putting AI into production also means being prepared to be held accountable for it.