A web dashboard that lets investigators upload police reports and call records to automatically map hidden connections between suspects and suspicious activities.
Ministry of Home Affairs · National Crime Records Bureau (NCRB), Women Safety Division · Software
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Decomposed from what the description asks for. Nothing added.
Data Ingestion Pipeline
Collects and processes structured and unstructured files like police reports and transaction records.
Entity Extraction Engine
Pulls out key entities such as people, locations, vehicles, and phone numbers using text processing.
Relationship Mapping Tool
Builds interactive visual graphs showing how different suspects, locations, and events are connected.
Influencer and Pattern Detector
Identifies key individuals in the network and flags unusual or suspicious activities.
Investigator Dashboard
Presents visual and analytical insights to help users query the data and review findings.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The evaluators will check if the system can successfully process unstructured data from multiple sources and generate accurate relationship maps and actionable insights for investigators.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.
What specific file formats or database schemas must the system support?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What exact algorithms or graph analysis models are expected?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What scale of data the system needs to handle during testing?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
Each one is quoted from a gap in the brief, not a guess about your team.
No measurable target
The description never states any measurable performance or accuracy targets for entity extraction or network analysis.
No specific user named
The description only refers broadly to investigators without naming a specific agency role or user profile.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.
Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.
Who has this problem, what already exists, and what you would have to find out.
The brief asks for data ingestion pipeline. How would you build that?
Decoded from SIH26189 itself — Collects and processes structured and unstructured files like police reports and transaction records. The brief asks for it by name.
The brief asks for entity extraction engine. How would you build that?
Decoded from SIH26189 itself — Pulls out key entities such as people, locations, vehicles, and phone numbers using text processing. The brief asks for it by name.
The brief asks for relationship mapping tool. How would you build that?
Decoded from SIH26189 itself — Builds interactive visual graphs showing how different suspects, locations, and events are connected. The brief asks for it by name.
The brief asks for influencer and pattern detector. How would you build that?
Decoded from SIH26189 itself — Identifies key individuals in the network and flags unusual or suspicious activities. The brief asks for it by name.
The brief asks for investigator dashboard. How would you build that?
Decoded from SIH26189 itself — Presents visual and analytical insights to help users query the data and review findings. The brief asks for it by name.
Where does your data come from — a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the evaluators will check if the system can successfully process unstructured data from multiple sources and generate accurate relationship maps and actionable insights for investigators.
This is the evaluator read for your problem statement, decoded from the brief's own wording.