ReBriNet (Resilience Bridge Net) is a TRL-6/7 solution by Social Tech Projects, created within the SecurIT project (2023–2024). It turns citizen inputs into actionable intelligence that emergency services and local authorities use to detect, triage, prioritize, and coordinate response actions. ReBriNet captures real-time signals (incident reports, geo-located surveys, community reporting), standardizes them into structured, time-stamped and geo-referenced data, and converts them into decision-ready outputs through AI analytics and GIS visualization. ReBriNet operationalizes actionable intelligence through an end-to-end chain: Signal capture: multi-channel reporting and feedback collection from the community. Standardization: harmonized data flows that reduce noise and enable consistent decision-making. Interpretation at scale: AI-driven topic and sentiment analysis that surfaces emerging issues, concerns, and escalation signals. Common situational understanding: GIS-based mapping that visualizes hotspots, clusters, and trend evolution in real time. Interoperable sharing: APIs and webhooks that integrate intelligence into existing emergency response systems, plus iframe embedding for rapid deployment. ReBriNet strengthens communications & information sharing by integrating information across channels, enabling interoperable communications, and delivering actionable intelligence to operational teams. Its automatic translation (100+ languages) and multi-language interface (20+ languages + customizable options) ensure inclusive participation and consistent guidance, improving public awareness and compliance during crises. ReBriNet thus standardizes the fluxes of information and decision-making, connecting civil society and responders through shared, intelligence-driven situational awareness.
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The ambition is to market ReBriNet (Resilience Bridge Net) as an actionable-intelligence layer that strengthens crisis preparedness, response, and recovery by transforming community inputs into decision-grade operational intelligence for first/second responders and local authorities. Building on the SecurIT project results, ReBriNet already delivers the core building blocks required for actionable intelligence: (1) an inclusive multimodal communication module with secure login, multi-stakeholder management (responders, local communities), a multilingual interface (13+ languages), and automatic translation from 100+ languages, (2) embedded responsive iframes and integration capabilities (APIs/webhooks) to connect with existing web and mobile emergency apps, (3) an AI topic-modeling and summarisation layer that aggregates crowdsourced data into prioritized themes, (4) real-time data integration and GIS map-based incident visualization to create a common operational picture, and (5) a self-triage tool based on geo-localised digital surveys (flooding, earthquake, fire/industrial disaster) that improves the speed and quality of field intelligence. The objectives of the proposal are to: - Operationalize actionable intelligence workflows end-to-end—from citizen signal capture to structured incident intelligence, prioritization, and responder dissemination; - Standardize information flows and decision-making across agencies through interoperable data formats, role-based dashboards, and integration into existing responder systems; - Improve common situational understanding by fusing community reporting, survey-based triage, and AI-derived insights into real-time GIS layers; - Increase public awareness and inclusion through multilingual, multi-channel alerts and bi-directional communication that reaches diverse communities; - Validate at scale with responder and citizen stakeholders, building on demonstrated demand (52 workshop participants, 32+ organizations involved)
ReBriNet introduces a distinct innovation in emergency management: it functions as an actionable-intelligence bridge between civil society and responders, converting fragmented community signals into structured, interoperable, decision-ready intelligence. 1) Operational intelligence ReBriNet applies AI topic modelling and summarisation to high-volume crowdsourced inputs, enabling responders to rapidly identify dominant needs, emerging risks, and escalation signals. This shifts crisis communication from passive reception of reports to prioritised intelligence outputs that support triage and resource allocation. 2) Inclusive intelligence at scale (multilingual by design). The solution embeds automatic translation for 100+ languages and a multilingual interface (13+ languages) so both incoming reports and outgoing guidance remain mutually understandable. This design removes a major operational barrier: language diversity no longer fragments situational awareness, improving coverage, representativeness, and public compliance. 3) Interoperability-first deployment ReBriNet provides responsive embedded iframes, plus APIs and webhooks, enabling fast integration into existing municipal portals and emergency apps on iOS/Android. This approach reduces procurement and integration friction and supports standardised information flows across stakeholders and systems. 4) Geo-referenced decision support. ReBriNet integrates citizen reporting and survey results into GIS-based incident mapping, producing real-time hotspot detection and trend monitoring. The result is a shared situational understanding that supports coordinated decisions across agencies. 5) Structured self-triage and rapid field intelligence. Digital geo-localised surveys (including auto-generated and custom-translated templates) support health-status triage and incident assessment for flooding, earthquakes, fires/industrial disasters.
ReBriNet resolves a core operational weakness in emergency management: responders lack a fast, inclusive, and interoperable way to convert community inputs into reliable, decision-grade intelligence. During crises, information is fragmented across channels and languages, arrives unstructured, and is difficult to validate, prioritise, and share across agencies. This slows triage, weakens coordination, and reduces public trust and compliance. ReBriNet strengthens operational capacity by addressing five concrete problems: - Information fragmentation and overload ReBriNet aggregates incident reports and community feedback and applies AI topic modelling and summarisation to transform high-volume messages into prioritised themes and operational signals, enabling quicker situational assessment and decision-making. -Lack of a shared operational picture ReBriNet integrates geo-referenced inputs and visualises them through a GIS-based interactive incident map, supporting hotspot detection, trend monitoring, and a common situational understanding across first/second responders. -Language barriers that reduce coverage and inclusiveness ReBriNet provides automatic translation (100+ languages) and a multilingual interface (20+ languages), ensuring both incoming reports and outgoing guidance remain understandable across diverse communities, improving reach and public awareness. - Slow deployment and limited interoperability with existing systems ReBriNet enables rapid adoption through responsive embedded iframes, and supports integration via APIs and webhooks, allowing to embed the solution into existing web/mobile emergency platforms and standardise information flows. - Insufficient structured data on people’s needs and impacts ReBriNet’s self-triage tool uses geo-localised digital surveys for flooding, earthquakes, and fires/industrial disasters to collect timely information on needs and health status, strengthening prioritisation and targeted assistance.
Our founding team combines deep expertise in software, data intelligence, and entrepreneurship. Simone Leomanni (CEO/Founder) brings 17+ years of software engineering experience and a strong background as a data and business intelligence architect. Luca Leomanni (CTO/Founder) has 18+ years of experience in software engineering, including 8 years working with deep tech, security and data driven technologies.
Our founding team combines deep expertise in software, data intelligence, and entrepreneurship. Simone Leomanni (CEO/Founder) brings 17+ years of software engineering experience and a strong background as a data and business intelligence architect. Luca Leomanni (CTO/Founder) has 18+ years of experience in software engineering, including 8 years working with deep tech, security and data driven technologies.