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Hyperlocal AI voter guide for midterm elections

Build a non-partisan, hyperlocal voter guide tool that takes a user's address and pulls their exact ballot (candidates, propositions, local measures) from public election data sources, then uses an LLM to summarize each candidate's platform, voting record, and funders in plain language with citations. This targets US voters who are overwhelmed by down-ballot races and are already turning to generic ChatGPT for help but getting vague or unsourced answers.

via Hacker News
Original post

What to build

A hyperlocal, non-partisan voter guide web app: a user enters their home address, the tool pulls their exact ballot (candidates, propositions, local measures, judicial races) from public election data sources, and an LLM summarizes each candidate's platform, voting record, and funders in plain language with inline citations.

Voters are already asking ChatGPT how to vote but getting vague, unsourced answers on down-ballot races; a specialized address-to-ballot tool with sourced LLM summaries fills that gap for the 2026 midterms.

Demand

Voters overwhelmed by local propositions, judicial races, and county contests — where information is scarce — are turning to generic chatbots out of necessity, not because those tools are built for the job.

  • Hacker NewsEngagement

    "People are asking ChatGPT to help them decide how to vote in the midterms" — 48 points, 79 comments on HN, indicating high discussion engagement around AI-assisted voting decisions.

  • Opportunity briefAnalysis

    Internal analysis identifies unmet demand: generic LLM chatbots give vague, unsourced answers on down-ballot races, and existing voter guides don't close that gap with sourced, conversational summaries.

Stack

  • Google Civic Information API
  • Ballotpedia API / data
  • OpenFEC API for funder/donor data
  • OpenAI or Anthropic API for summarization with citations
  • Next.js + Vercel for the web app
  • Supabase or Postgres for ballot/address caching

Solo + AI difficulty

The hard part is sourcing and normalizing fragmented down-ballot data across thousands of counties — expect to start with a handful of states with clean open data (e.g. via Google Civic Info API or Ballotpedia) rather than full US coverage; the LLM summarization and citation layer is comparatively easy with current APIs. Realistic MVP for one state or metro area: 2-4 weeks; full non-partisan fact-checking rigor to avoid misinformation risk adds meaningfully more time.

Entry threshold
No capital or licensing needed; a solo builder can combine public election data APIs (Ballotpedia, Vote411, state election sites) with an LLM summarization layer to ship an MVP for key states within 2-3 weeks before the midterms.
Window
3-5 weeks (through the Nov 2026 midterms, recurring every election cycle)

Where to find first users

  • Reddit (r/politics, local city/state subreddits close to Nov 2026 election day)
  • Product Hunt launch timed before early voting starts
  • Local news and civic tech newsletters (e.g. Democracy Works, civic tech Slack/Discord communities)
  • Hacker News Show HN post, given existing HN engagement on the underlying signal

Competitors

Counter-signals & risks

  • Public election data for down-ballot races is fragmented and inconsistent across counties and states, making accurate automated aggregation difficult.

  • LLM-generated political summaries risk factual errors or hallucinated voting records, which could undermine trust in a tool branded as non-partisan and create misinformation exposure.

  • Vote411 and BallotReady already provide hyperlocal ballot information, raising the bar for differentiation and user acquisition.

Original title: People are asking ChatGPT to help them decide how to vote in the midterms

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Hyperlocal AI voter guide for midterm elections — Nichr