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ElectionChain: Certified Data Reconciliation & Chain-of-Custody Service

A human-led verification service where trained election auditors physically visit polling stations and election offices to reconcile official paper forms (tally sheets, voter rolls, ballot counts) against digital records in real-time. The service produces a signed, notarized reconciliation report that identifies discrepancies, flags which source is authoritative (based on documented chain-of-custody), and provides legal standing for disputes or recounts.

SERVICE

34 weeks • 70% confidence

Value Proposition

Eliminates reliance on unverified digital sources by anchoring truth in physical documents + human verification. Produces legally defensible audit trails that courts recognize. Operates in real-time during critical election windows when officials are most vulnerable to pressure. Beats DIY spreadsheet comparison because it's independent, certified, and creates liability for falsification.

Target Audience

Election commissions, regional election boards, and international election observer organizations in countries with weak digital infrastructure or high fraud risk (sub-Saharan Africa, South Asia, Latin America)

Key Features

  • On-site physical verification of paper tally sheets against digital databases
  • Chain-of-custody documentation for all data sources
  • Notarized reconciliation reports with auditor signatures and timestamps
  • And more, with full implementation detail...

Tech Stack

Mobile form tool (Google Forms, Kobo Toolbox for offline-capable forms) Cloud spreadsheet backend (Google Sheets, Airtable for real-time data aggregation) Photography documentation (mobile camera + metadata preservation) Notarization coordination (local legal partnerships, no tech required)
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Original Problem

Election officials and auditors struggle to verify election data accuracy across multiple sources

Election administrators and observers need to reconcile and verify election results from official forms against data in spreadsheets and databases, but lack reliable methods to identify discrepancies and validate which source is authoritative. Current solutions fail because they rely on manual comparison of unverified data sources, making it difficult to detect fraud, errors, or manipulation in real-time during critical election periods.

Score: 57.4% • 1 demand signal

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