AI readiness and strategy
Scattered initiatives, expectations that differ between departments, and difficulty deciding where to start without committing resources to pilots that never scale.
Services →AI, data and governance consulting
Strategy, data and governance to bring AI into operations.
We work with leadership to prioritise initiatives, organise the capabilities they require, and direct their implementation alongside internal teams and the vendors the organisation already works with.
325controls in the methodological catalogue
G0–G3maturity levels, from informal use to auditable operation
3reference frameworks: ISO/IEC 42001, EU AI Act and NIST AI RMF
11sector modules in the framework
These figures describe the scope of the framework. They are not client results or commercial metrics.
Three lines of work
They can be engaged separately or combined. The starting point depends on each organisation's situation.
Data and operations
The necessary data exists but is scattered, without clear owners or quality controls, and the processes that should use it are not defined end to end.
Services →Governance and risk
AI systems already in use with no approved policy, no inventory, no risk classification and no evidence to answer an audit, a funder or an oversight body.
Services →How we intervene
A four-stage path with a flexible entry point. Governance is not a final stage: it runs through the whole engagement.
Diagnose
Understand the real starting point, not the declared one.
Prioritise
Decide where to intervene first.
Accompany implementation
Ensure what was prioritised is executed and reaches operations.
Measure and improve
Know whether it works and correct in time.
Contexts we recognise
Sectors where the track record of the firm's members makes it possible to understand the problem before proposing a solution.
Public sector
Data spread across departments with legacy systems and no single owner.
Health
Handling sensitive personal data in clinical and administrative processes.
Water and sanitation
Utilities with uneven capabilities and a need for territorial integration.
Transport and infrastructure
Continuous operation with high exposure to the user experience.
Who we work with
Mid-sized companies
Leadership that needs to organise AI usage, decide priorities and avoid decisions scattered across departments.
Large companies and regulated sectors
Data, risk and technology functions that must demonstrate control over systems already in use.
Public bodies
Teams accountable to oversight bodies, multilateral funders and citizens.
What the work rests on
AGORA works with its own AI governance framework and a supporting platform. The framework is the methodological backing; the platform organises follow-up. Neither replaces professional judgement.
- A methodological catalogue of 325 controls, built on ISO/IEC 42001, the EU AI Act and NIST AI RMF.
- A four-level maturity model, from informal use to auditable operation.
- Control selection proportional to each organisation's risk and context.
Who leads the firm
Pedro Pistoni, lawyer and MBA, with more than fifteen years at the intersection of regulation, data and operations across Latin America's public and private sectors.
Insights
Writing on AI governance, data and operations.
No pieces published in this language yet
We are preparing the first pieces to publish here. In the meantime, Pedro Pistoni writes regularly about AI governance, data and operations on LinkedIn.
These pieces are published in Spanish. See the list in Spanish (12)
See his posts on LinkedIn (opens in a new tab)
You can also review the services or write to us about a specific case.
Free exploratory assessment
Twelve questions about AI and data use in your organisation. An AGORA professional reviews them and sends you a written response by email.
Sector references correspond to the professional trajectory of the firm's members, not to AGORA Advisory contracts.