Enhance democratic transparency
Track how policy priorities change, who supports or opposes them, and how public decisions are shaped over time.
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Politicker.ai uses advanced AI to analyse policymaking discourse. Our data-driven insights help researchers, journalists, and citizens understand what's happening in Parliament. If you want to collaborate or hire our services, get in touch!
Answer Quality and Deflection
Mission & Key Objectives
We use large-scale political research, data processing and AI to turn legislative debate into clear, accessible intelligence for organisations and citizens.
Reveal policy discourse
Surface the arguments, narratives and connections defining debate across legislative transcripts, reports and public records.
Synthesise complex political debate
Convert high-volume political sources into concise, actionable evidence that organisations and citizens can use.
Capabilities
We provide specialised services at the intersection of political science and data technology for researchers, analysts and policy professionals.
LLM-Assisted Textual Analysis
Our proprietary pipelines use advanced large language models to code, categorise and analyse legislative transcripts, committee reports and related political sources at scale.
Researchers can move from high-volume source material to structured evidence without months of manual review.
Evolving Reports
We provide regularly refreshed reporting on policy discourse through structured datasets and clear visualisations.
Users can follow changing salience, emerging arguments and the legislators shaping each issue.
Instant Access
Technically enabled teams can use our API to monitor political discourse independently and in near real time.
Structured outputs integrate with existing research, analysis and reporting workflows.
Step-by-Step Guide
Our workflow turns political source material into structured, tested and accessible intelligence.
Step 1
Load political sources
Policymaking documents and transcripts are manually or automatically loaded into a structured database.
Step 2
Structure units of analysis
An LLM call identifies units of analysis, structuring text for quantitative analysis before each unit is entered into a structured database.
Step 3
Run layered LLM analysis
Each unit is subjected to multiple LLM calls that determine:
- Policy agendas
- Types of language
- Keywords and arguments
- How issues are framed or distorted
- Mentions of places, organisations and people
- Structured data for API or bespoke dashboard access
Step 4
Scrutinise and refine
Our methodology is rigorously scrutinised and refined. Samples are examined and developed to be statistically robust using human-to-AI reliability testing.
Case Study
Policy Agendas & MP Behaviour in PMQs
Our LLM-assisted analysis of Prime Minister’s Questions (PMQs) transcripts from 1997 to the present reveals how policy agendas have changed over time and how questions reflect public priorities.
Explore the changing salience of major policy pillars across PMQs, including the issues raised with the Prime Minister and the priorities reflected in parliamentary exchanges.
Parliamentary Issue Tracker
Top Issues
Latest available snapshot
Blogs
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How Reliable is the Politicker Method?
A new platform harnessing AI to produce reliable data on Parliament
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The New Age of Advice: How AI is Upending the Traditional Consultancy Model
This article discusses the shift in the strategic consultancy industry, highlighting how traditional, manpower-heavy models are becoming outdated. The core argument is that clients are now seeking cheaper, AI-powered solutions to navigate the complexities of the AI revolution. The article introduces Politicker as a prime example of this new model. Unlike traditional consultancies that rely on billable hours, Politicker offers an automated data feed that provides strategic advice on demand.