From documents to institutional knowledge
Public bodies hold decisions, rules, contracts, registries and systems. AI becomes useful when these form a coherent, time-aware and auditable institutional context.
AI IN PUBLIC ADMINISTRATION
Artificial Intelligence in Public Administration
Public-sector AI requires more than text generation: institutional context, evidence, transparency, accountability and meaningful human oversight.
Governed neurosymbolic AI combines language-model capabilities with controlled institutional knowledge and traceable sources.
Critical requirements
A public decision-support system must separate information, reasoning, authorisation and approval.
- Evidence provenance and integrity
- Roles, authority and temporal validity
- Traceable reasoning and validation
- Human oversight and auditability
From probable answer to grounded conclusion
DeepThink proposes interpretations and syntheses. DeepCore controls admissible institutional data and checks whether claims remain grounded.
PRACTICAL ANSWERS
Frequently asked questions
How is this different from a public chatbot?
A chatbot mainly answers from text. Institutional intelligence also models authority, decisions, temporal validity, evidence and administrative entities.
Is human oversight required?
Yes. Oversight must be meaningful, proportionate to risk and preserve clear accountability.
Can it support ministries and public bodies?
Yes, with organisation-specific ontology, permissions, sources, workflows and governance rules.
MDIP
From fragmented information to evidence-grounded public decisions.
MDIP connects strategy, programmes, projects, contracts, finance and institutional evidence in one governed decision-support environment.