Ordinal

Ordinal

Ordinal AI is an AI-powered research assistant for municipal governments that uses Retrieval-Augmented Generation (RAG) to deliver fast, accurate answers grounded in approved city documents, GIS data,

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What is Ordinal?

Ordinal is an AI research assistant designed specifically for municipal governments. It uses Retrieval-Augmented Generation (RAG) to answer questions by pulling information directly from your city's approved documents, codes, GIS data, meeting notes, ordinances, and archives. Rather than generating answers from general training data, it grounds responses in your actual institutional knowledge, reducing errors and ensuring compliance with local regulations. The tool deploys quickly, with most councils operational within two weeks and only 45 minutes of onboarding required. It centralises scattered information across departments, automatically updates when documents change, and tracks who accessed what through audit logs. Ordinal doesn't replace staff or decision-making; it handles the research legwork so employees can focus on analysis and action.

Key Features

Retrieval-Augmented Generation

answers grounded in your approved city documents and data rather than general AI training

Quick deployment

operational in as little as two weeks with minimal setup time

Document integration

connects to municipal codes, ordinances, resolutions, GIS data, meeting notes, and archives

Role-based access controls

restrict who can see which documents with built-in permission management

Audit logs

track all queries and access for transparency and compliance

Auto-updating

documents and codes refresh automatically so answers stay current

Pros & Cons

Advantages

  • Reduces time spent searching through scattered documents and institutional knowledge
  • Answers cite specific approved sources, making it easier to verify accuracy and comply with regulations
  • No per-seat pricing means you can roll it out citywide without scaling costs dramatically
  • Quick implementation means you see value within weeks rather than months

Limitations

  • Effectiveness depends on the quality and completeness of documents you feed it; gaps in your records will limit its usefulness
  • Requires initial effort to integrate with existing systems and ensure all relevant documents are uploaded
  • As a municipal-specific tool, it has a narrower audience than general-purpose AI assistants

Use Cases

Planning and zoning staff answering questions about development codes and permit requirements without manually flipping through documents

Finance departments researching municipal ordinances and resolutions related to budgets or spending authority

Customer service teams providing consistent, accurate answers about city policies and procedures

Cross-departmental research on past decisions, meeting outcomes, or regulatory compliance questions

New staff onboarding, allowing them to quickly find answers to common questions about city operations