PROBLEM STATEMENT
Agentic Child Protection Investigation
Assistant (ACPIA)
PROBLEM OVERVIEW
Child protection investigations often require the examination of large volumes of digital evidence originating from multiple sources and formats. Investigators must rapidly identify relevant information, establish connections between disparate data points, generate actionable leads, and support victim safeguarding efforts. The increasing scale, diversity, and complexity of digital evidence presents significant challenges for timely and effective investigations.
THE CHALLENGE
Design and develop an AI-powered investigation support platform that assists authorized agencies in the efficient analysis, correlation, and interpretation of digital evidence related to child protection cases. The solution should leverage advanced technologies to transform large volumes of structured and unstructured data into meaningful insights, enabling investigators to focus on high-priority leads and informed decision-making.
KEY AREAS FOR INNOVATION
01
Automated analysis and categorization of digital content for faster threat assessment.
02
Identification of potentially relevant or high-risk material in digital evidence.
03
Correlation of information across multiple digital sources and platforms.
04
Extraction of contextual insights and details from multimedia files.
05
Analysis of digital footprints and online activity patterns of targets.
06
Metadata extraction, enrichment, and network relationship mapping.
07
Detection of manipulated, synthetic, or AI-generated content.
08
Reconstruct timelines and correlate events for case buildups.
09
Intelligent search, filtering, and rapid information retrieval.
10
Automated summarization and generation of case reports.
11
Advanced risk assessment and prioritization of investigative leads.
12
Cross-source intelligence fusion and deep knowledge discovery.
01
Technology Areas
Participants are encouraged to explore Artificial Intelligence, Agentic AI Systems, Computer Vision, Audio Intelligence, Digital Forensics, Large Language Models (LLMs), Knowledge Graphs, Data Analytics, Explainable AI, and Advanced Data Correlation techniques.
02
Expected Outcome
The proposed solution should significantly improve the efficiency and effectiveness of digital evidence analysis by reducing manual effort, accelerating the discovery of critical information, and enhancing investigative workflows. The platform should provide investigators with timely, actionable intelligence that supports victim protection, informed decision-making, and faster case progression while maintaining appropriate human oversight throughout the process.
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Hac'KP 2026 Core Challenge
Child protection investigations often require the examination of large volumes of digital evidence originating from multiple sources and formats. Investigators must rapidly identify relevant information, establish connections between disparate data points, generate actionable leads, and support victim safeguarding efforts. The increasing scale, diversity, and complexity of digital evidence presents significant challenges for timely and effective investigations.
Design and develop an AI-powered investigation support platform that assists authorized agencies in the efficient analysis, correlation, and interpretation of digital evidence related to child protection cases. The solution should leverage advanced technologies to transform large volumes of structured and unstructured data into meaningful insights, enabling investigators to focus on high-priority leads and informed decision-making.
01
Automated analysis and categorization of digital content for faster threat assessment.
02
Identification of potentially relevant or high-risk material in digital evidence.
03
Correlation of information across multiple digital sources and platforms.
04
Extraction of contextual insights and details from multimedia files.
05
Analysis of digital footprints and online activity patterns of targets.
06
Metadata extraction, enrichment, and network relationship mapping.
07
Detection of manipulated, synthetic, or AI-generated content.
08
Reconstruct timelines and correlate events for case buildups.
09
Intelligent search, filtering, and rapid information retrieval.
10
Automated summarization and generation of case reports.
11
Advanced risk assessment and prioritization of investigative leads.
12
Cross-source intelligence fusion and deep knowledge discovery.
01
Participants are encouraged to explore Artificial Intelligence, Agentic AI Systems, Computer Vision, Audio Intelligence, Digital Forensics, Large Language Models (LLMs), Knowledge Graphs, Data Analytics, Explainable AI, and Advanced Data Correlation techniques.
02
The proposed solution should significantly improve the efficiency and effectiveness of digital evidence analysis by reducing manual effort, accelerating the discovery of critical information, and enhancing investigative workflows. The platform should provide investigators with timely, actionable intelligence that supports victim protection, informed decision-making, and faster case progression while maintaining appropriate human oversight throughout the process.
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