Public institutions
Intelligence by project
and by municipality
Perception, risk, and public acceptance
of each initiative.
A public initiative is debated in the municipality it affects before it is debated anywhere else. That is why general opinion is not enough: what the people living next to each project think matters too.
The platform reads general perception and the perception in each municipality, so the institution can get ahead of a problem instead of reacting to it.
Who the platform listens to
Beyond the general conversation, the platform reads what is published openly about an initiative from the quarters that shape opinion: local bodies, civic organizations, businesses, and the media. They are different audiences, and what one says cannot be inferred from what the others say.
Sources the platform reads
Media, social, search engines, AI assistants, and proprietary data.
60 min
shortest data refresh cycle
What a public institution gets
Perception dashboard
It brings the perception index, public acceptance, and media coverage into one view. Coverage is measured by reach, tone, and framing. It shows where the institution stands as a whole before looking at each project.
Project profile
Each initiative has its own profile, with its strengths, its risks, and the priority it warrants. Projects are compared with one another, which shows where attention is needed first.
Municipality and district
The same reading is taken down to each municipality and each district, which is where an initiative is debated. The result points to the places that need attention.
Emotional climate
The emotional spectrum is read by topic and by audience. It separates hope, distrust, pride, and frustration, which call for different responses.
Alerts
Each incident arrives as an alert with its severity and the protocol that applies to it. An internal alert comes with context, history, and a recommended response.
Verification
It checks claims against traceable evidence. That gives the institution a fact base for responding quickly when a fact is called into question.
How the platform works
The platform works in a cycle of seven steps: listen, normalize, understand, anticipate, decide, act, and learn. Capture of social, media, and proprietary sources is continuous, and every source is mapped to one common schema before it is analyzed. Every action feeds the next round of listening.
Six specialized AI agents analyze the same signal. One detects weak signals and volume anomalies, another classifies the emotional spectrum, and another extracts frames, arguments, and key actors; the rest cover artificial activity, verification, and the link to the historical record.
The six reports are cross-checked before they reach a person.
Where to focus communication,
and when to step in.
With that reading, the institution decides where to focus its communication and when to step into an emerging issue.
Not every signal calls for action, and not every action should be public. Each signal ends in one of three outcomes, based on thresholds.
Silence
Noise is tagged and archived. This is the default.
Internal alert
With context, history, and a recommended response.
Public action
Always previewed before it is published.
How an AI assistant
describes you.
First impressions no longer come only from a search engine. They also come from an assistant. Anyone asking about an organization already gets an answer written by an AI, and the institution needs to know what it says and which sources it draws on.
The platform audits every search result and every assistant answer, fills information gaps with original sources, and measures regularly, model by model, what the assistants answer.
Security, traceability,
and human decision
Access is by invitation only, with MFA and enterprise SSO, and there are six roles with granular permissions by section. Every action and every AI query is logged. Data is encrypted in transit and at rest, and GDPR and Spain’s LOPDGDD are applied by design.
GDPR and the EU AI Act ask where each conclusion comes from and who makes the call. Here, that is built in from the start.
Every fact has a source.
The platform proposes.
A person decides.
Nothing ships unreviewed.
AI amplifies human judgment. It does not replace it.
In production in six months.
Typical schedule. Two-week sprints, a demo every two weeks, and incremental deliveries you can verify.
Months 1–2
Foundations
Discovery, architecture, corporate access, and the first modules in use.
Months 3–4
Measurement
Analysis modules, the first version of the AI, and the executive dashboard.
Months 5–6
Optimization
Early warnings, user testing, training, and launch.
Afterward
Evolution
New modules, API integrations, and handover to full autonomy.
Frequently asked questions
How is this different from a listening tool or a periodic report?
A listening tool delivers a mentions dashboard, which counts but does not interpret, and a periodic report arrives after the fact. The platform is software purpose-built for the institution: it captures its sources, analyzes them with specialized AI agents, and delivers a recommended decision traceable to the source data.
How local does the reading get?
Down to the municipality and the district. The reading of the institution as a whole is repeated in each of them and points to the places that need attention.
Does the platform publish or respond on its own?
No. The platform proposes and a person decides; nothing ships unreviewed. Silence is the default. Whatever is published, the institution publishes, through its own channels and after reviewing it.
How do we know where each conclusion comes from?
Every fact has a source, and the recommended decision is traceable to the source data. Every action and every AI query is also logged.
How often is the data updated?
The refresh cycle is set for each project, at the pace that is useful to it; the shortest is 60 minutes. Capture of social, media, and proprietary sources is continuous.
How long does it take to be up and running?
The typical schedule is six months, with the first modules in use in months 1 and 2. Work runs in two-week sprints, with a demo every two weeks and incremental deliveries the institution can verify.
We do not name our clients.
Confidentiality is part of the service: here we speak of industries.