AI Intelligence Engine Specification

Home / AI Intelligence Engine / AI Intelligence Engine Specification

AI Intelligence Engine Specification

Overview

The AI Intelligence Engine is a modular intelligence and analytics framework that provides artificial intelligence capabilities for detecting promises, analyzing policy statements, identifying contradictions, processing documents, mapping relationships, generating citations, and producing trend summaries.

The module serves as the analytical foundation for transparency, accountability, research, and investigative platforms by transforming unstructured information into structured, verifiable intelligence.

This specification defines the complete implementation requirements, architecture, workflows, operational procedures, and governance standards necessary to build a fully compliant AI Intelligence Engine.

Objectives

The system shall:

Detect promises and commitments from natural language.
Compare speeches against policies and actions.
Detect semantic contradictions.
Compare stated intentions with voting behavior.
Parse structured and unstructured filing documents.
Build relationship maps between entities.
Generate automated source citations.
Produce intelligence summaries and trend reports.
Maintain complete evidence traceability.
Support human review and verification.

Scope

The specification applies to:

Politicians
Government officials
Candidates
Political parties
Nonprofits
Government agencies
Corporations
Lobbyists
Advocacy organizations
Media publications
Public records repositories

System Architecture

Core Components

Data Collection Layer

Responsibilities:

Data ingestion
Data normalization
Source validation
Metadata extraction

Intelligence Processing Layer

Responsibilities:

NLP processing
Entity extraction
Relationship resolution
Contradiction analysis
Trend generation

Evidence Layer

Responsibilities:

Source attribution
Citation management
Evidence storage
Confidence scoring

Knowledge Graph Layer

Responsibilities:

Entity relationships
Historical timelines
Cross-reference analysis
Network generation

API Layer

Responsibilities:

Search endpoints
Analytics endpoints
Export endpoints
Reporting endpoints

User Interface Layer

Responsibilities:

Intelligence dashboards
Review workflows
Entity visualization
Citation review
Trend reports

Deployment Requirements

Supported Environments

Linux
Kubernetes
Docker
Virtual machines
On-premises deployments
Cloud deployments

Recommended Infrastructure

API Servers

Minimum: 4 CPU
Recommended: 8 CPU
Memory: 16 GB minimum

Processing Workers

Minimum: 8 CPU
Recommended: 16 CPU
Memory: 32 GB

Database

PostgreSQL
Minimum storage: 500 GB SSD

Search Engine

OpenSearch
Elasticsearch-compatible engines

Object Storage

S3-compatible storage
Self-hosted object storage

Required Services

Databases

PostgreSQL
Redis
OpenSearch

AI Services

Embedding service
Language model service
OCR service
Speech-to-text service

Directory Structure

/api
/workers
/nlp
/parsers
/knowledge_graph
/citations
/reports
/models
/storage
/config
/logs
/tests
/docs

Database Schema

Entity Table

Fields:

id
entity_type
name
aliases
description
confidence_score
created_at
updated_at

Source Table

Fields:

id
source_type
title
url
publication_date
publisher
checksum
metadata

Document Table

Fields:

id
source_id
document_type
file_location
text_content
language
processed_at

Promise Table

Fields:

id
entity_id
promise_text
category
confidence_score
source_id
status

Policy Table

Fields:

id
title
description
category
source_id

Contradiction Table

Fields:

id
entity_id
contradiction_type
evidence
confidence_score

Vote Table

Fields:

id
entity_id
bill_id
vote
date

Relationship Table

Fields:

id
source_entity
target_entity
relationship_type
confidence_score
source_id

Citation Table

Fields:

id
source_id
evidence_id
citation_text
citation_url

Trend Table

Fields:

id
entity_id
metric_name
metric_value
measurement_date

Entity Relationship Model

Relationships:

Entity → Promise
Entity → Vote
Entity → Relationship
Entity → Contradiction
Entity → Source
Source → Document
Source → Citation
Policy → Source

Data Ingestion Requirements

Supported Sources

Government websites
Legislative databases
SEC filings
Campaign websites
Press releases
Speeches
Debate transcripts
Social media posts
News publications
Nonprofit filings
Corporate filings
Public records

Ingestion Workflow

Retrieve source.
Validate source authenticity.
Download content.
Generate checksum.
Extract metadata.
Store source.
Queue processing jobs.
Generate embeddings.
Update knowledge graph.

Natural Language Promise Detection

Purpose

Identify promises, commitments, pledges, goals, and policy intentions.

Detection Rules

Indicators include:

“I will”
“I promise”
“I pledge”
“I intend”
“I plan”
“We will”
“My administration will”

Processing Steps

Sentence segmentation.
Named entity recognition.
Intent classification.
Promise extraction.
Confidence scoring.
Human review.

Speech-to-Policy Comparison

Purpose

Determine whether policy actions align with public statements.

Workflow

Parse speech.
Extract commitments.
Retrieve policy actions.
Generate semantic embeddings.
Calculate similarity scores.
Produce alignment score.
Store evidence.

Output Categories

Fully Aligned
Partially Aligned
Contradictory
Insufficient Evidence

Semantic Contradiction Detection

Purpose

Identify inconsistencies between statements, policies, and actions.

Contradiction Categories

Statement reversal
Policy reversal
Voting contradiction
Timeline contradiction
Public versus private statement conflict

Workflow

Retrieve historical statements.
Generate embeddings.
Compute semantic similarity.
Identify opposing positions.
Calculate contradiction confidence.
Generate evidence package.
Queue for review.

Voting Intent Comparison

Purpose

Compare promises and statements against voting history.

Workflow

Extract promise.
Identify relevant legislation.
Retrieve voting records.
Compare outcomes.
Score alignment.
Produce report.

Filing Document Parsing

Supported Documents

SEC filings
Financial disclosures
Ethics disclosures
Corporate registrations
Campaign finance reports
Nonprofit filings
Lobbying reports
Legislative documents

Parsing Workflow

Retrieve document.
OCR if necessary.
Extract text.
Classify document.
Extract entities.
Extract dates.
Extract financial values.
Store structured records.

Relationship Mapping

Purpose

Build a graph of interconnected entities.

Relationship Types

Employment
Ownership
Board membership
Advisory role
Family relationship
Campaign donation
Lobbying relationship
Political affiliation
Business partnership
Contract relationship

Workflow

Extract entities.
Resolve aliases.
Calculate confidence.
Build graph edge.
Store relationship.
Update graph indexes.

Knowledge Graph Requirements

Capabilities:

Historical relationships
Temporal analysis
Multi-hop queries
Entity clustering
Influence scoring
Relationship strength scoring

Automated Source Citation Linking

Purpose

Every intelligence finding must be supported by evidence.

Citation Requirements

Each citation shall contain:

Source title
URL
Publication date
Publisher
Archived location
Retrieval date
Confidence score

Citation Workflow

Generate finding.
Retrieve evidence.
Link sources.
Verify accessibility.
Generate citations.
Store references.

Trend Summaries

Purpose

Produce summaries of evolving behaviors and patterns.

Trend Workflow

Aggregate events.
Generate timelines.
Calculate metrics.
Identify anomalies.
Generate summary.
Store reports.

Intelligence Scoring

Confidence Levels

Very High
High
Medium
Low
Insufficient Evidence

Confidence Inputs

Source reliability
Number of sources
Semantic certainty
Data freshness
Human verification status

Human Review Requirements

Human review is mandatory for:

Contradiction findings
Promise reversals
High-impact reports
Low-confidence results
Relationship disputes

Review Workflow

Review evidence.
Review citations.
Validate findings.
Approve or reject.
Document decision.

Audit Requirements

The system shall maintain:

Processing logs
Source history
Review history
Model versions
Citation history
Evidence history

Security Requirements

Encryption at rest
Encryption in transit
Role-based access control
API authentication
Immutable audit logs
Rate limiting
Backup procedures

Performance Requirements

The system should support:

Millions of documents
Millions of entities
Real-time ingestion
Distributed processing
Horizontal scaling
Incremental indexing

API Requirements

Search API

Entity search
Document search
Citation search
Relationship search

Analytics API

Promise analysis
Contradiction analysis
Voting analysis
Trend analysis

Export API

JSON
CSV
PDF
Graph exports

Testing Requirements

Unit Tests

NLP processing
Entity extraction
Relationship mapping
Citation generation

Integration Tests

Ingestion pipeline
Search engine
APIs
Review workflows

Performance Tests

Large datasets
Concurrent requests
Graph traversal
Batch processing

Compliance Requirements

Implementations must provide:

Reproducible findings
Transparent evidence chains
Explainable AI outputs
Human review capabilities
Citation traceability
Audit logging

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
Required attribution:
Roxanne Ardary
https://www.roxanneardary.com/

Optional

Specification Branding License (SBL)
Attribution-free commercial deployment
Pricing based on scale, usage, and deployment scope
https://roxanneardary.com/ai-intelligence-engine/

License & Notice Requirements

AI Intelligence Engine Specification is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

By contributing to any Open Arsenal project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to Roxanne Ardary and roxanneardary.com.
AI Intelligence Engine specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – ActionCheck

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – March 10, 2026
Created the repository for ActionCheck. Designed the platform to track politicians’ promises, votes, financial activity, and board memberships for public accountability.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.