Data Friendly Space has just launched GANNET Deep Dive, a new feature that brings together quantitative data analysis and AI-powered research for crisis response. Now, practitioners can use simple, conversational questions to run statistical analyses that blend both qualitative and numerical insights from reliable humanitarian sources.
GANNET Deep Dive addresses a persistent challenge in humanitarian operations: the time-consuming transition from data aggregation to actionable insights. Previously, practitioners had to navigate multiple tools, request AI-generated context, download datasets, perform spreadsheet calculations, and manually synthesize results.
"Professionals working in crisis response shouldn't need to be data scientists to access the information that drives their decisions," said Nayid Orozco, Chief Product Officer at Data Friendly Space. "Deep Dive eliminates the technical barriers between asking a question and getting a comprehensive, sourced answer."
The system operates alongside GANNET's existing Quick Flight mode, which provides rapid qualitative insights. Deep Dive adds direct integration with the Humanitarian Data Exchange (HDX-HAPI), a global repository of vetted humanitarian data. This allows users to query these verified datasets using natural language, with additional quantitative datasets to be included in the future.
Users can ask questions such as "Compare food insecurity rates between Somalia and Yemen this year" or "Show me trends in displacement numbers across Sudan" and receive both statistical findings and contextual analysis with complete source attribution.
The feature automatically builds analytical context from dataset metadata, enabling it to process complex humanitarian data without requiring users to specify technical parameters or variable names.
GANNET Deep Dive maintains data integrity by preserving raw numerical data in its original form and providing complete citation chains for all analytical outputs. This transparency addresses the trust deficit identified in user research on AI-assisted analysis tools and responds to the increased accountability pressures faced by agencies. By linking every statistic back to its source dataset, GANNET Deep Dive supports the growing demands from donors and auditors for rigorous evidence.
"Every statistic links back to its source dataset," the team explained. "For evidence-based reporting and donor communications, practitioners need to know not just what the AI found, but where it found it." Additionally, our commitment aligns with sector initiatives such as the Grand Bargain, ensuring that our users meet their accountability obligations.
GANNET Deep Dive is available now through the GANNET Virtual Assistant platform. If needed, the Data Friendly Space team is available for training and questions. We plan to add quantitative data sources and transparency into the reasoning trail in upcoming releases, providing step-by-step explanations of analytical processes and statistical methodology.
