Technology & AI Policy

Tickstock operates at the leading edge of journalism, automation and content production technologies. This page covers the platform behind the publication. Here, you can learn more about what it does, how it produces content, the safeguards on bias and quality, and how reader data is handled.

Last updated 22 May 2026

The Platform

The TickStock Newsroom leverages an AI-assisted content production system that supports and powers a substantial portion of Tickstock's daily output. It is a proprietary newsroom automation platform that combines agentic news discovery, structured source ingestion, large-language-model content drafting, data operations, stringent quality guardrails and testing, as well as knowledge and intelligence infrastructure.

Core capabilities:

  • Continuous and agentic monitoring of news discovery vectors
  • Structured ingestion of source inputs including but not limited to research notes, market commentary, data and primary corporate communications
  • AI-powered content drafting using leading large-language-model systems
  • A two-pass quality control process before publication
  • A Knowledge Graph that provides structured verification context on every covered entity
  • Human editors have oversight and the ability to intervene at every layer

Our technology stack enables fast, accurate and comprehensive coverage of fast-moving market sectors at a quality standard retail investors deserve. It means we can deploy significantly more sustained editorial capacity than any small team can supply only by organic hands. Our approach, using our proprietary solutions, allows us to augment human judgment with automation. Our machines handle volume and precision; our humans handle nuance, judgment, and accountability.

Content Production

The full multi-step workflow and platform capabilities include but are not limited to source discovery, semantic and contextual awareness, content drafting, quality control and evaluation, human review, and publication routing, and are documented in more detail via the AI disclosure policy page. The content verification details, including the knowledge graph structure, are on the fact-checking policy page.

Every published piece of content is the product of a human editor-in-the-loop system. AI-assisted articles carry the TickStock Newsroom collective byline. Guest contributor and columnist pieces are bylined to the named author, and whilst they are not produced through the core AI-powered pipelines, they are also supported by publishing and knowledge systems that may leverage functional automation and AI tools. On-page labelling and disclosures are in place on every article to make clear all necessary distinctions.

What Gets the Newsroom Treatment, and What Doesn't

AI-assisted Newsroom content is suited to: breaking news, structured and regulated news announcements, corporate statements, earnings releases, trading updates, director dealings, buybacks, dividends, capital raises, M&A announcements, regulatory developments, and structured sector or market updates.

Original investigative reporting, opinion, expert analysis, interviews, coverage of contested issues, and corrections are human-authored.

More insight is available on the AI disclosure policy page.

Bias Mitigation

Drafting parameters in our content systems explicitly prohibit editorialising, inflammatory language, speculative claims, ramping or talking down a stock, and the insertion of cultural or political bias.

We monitor for drift through continuous audits of generated content, source diversity analysis, reader feedback evaluation, and continuous refinement of drafting parameters. When AI output exhibits potential issues, human editors review the source material, adjust parameters where systematic patterns emerge, manually edit problematic content, and flag issues for platform improvement.

Coverage of Technology Vendors

Tickstock uses commercial large-language-model APIs while also potentially covering the providers (and their listed parents) as news subjects. We manage the conflict the same way we manage any vendor relationship — no editorial coordination with vendors, identical coverage standards, and disclosures included where editorially relevant. Full treatment on the ethics policy page.

Data Privacy

What we collect

Tickstock collects minimal user data; it may include standard web analytics (page views, traffic sources, country-level location), email addresses for newsletter subscribers (only if users voluntarily provide them), and engagement metrics on social channels.

What we don't do with your data

Tickstock does not use personal user data to train AI models, sell user information to third parties, or share data with AI providers.

AI training

The platform uses commercial LLM APIs for content production. As of the last update of this page, those APIs do not use Tickstock's content or any reader data for model training. We monitor provider policies and will update if that changes.

Limitations

Verification at the quality control layer can confirm that an article's claims are supported by the source material it draws from. It cannot catch errors in the underlying source material itself, replace the editorial judgment that decides whether a story is worth publishing, or replace the broader fairness and balance considerations in the human editorial layer. When errors reach publication, we correct on the same standards as any other content. For more insight, see the corrections policy page.

Future Evolution

AI technology evolves quickly. We commit to disclosing major platform changes to readers, evaluating new AI capabilities against journalism standards before adopting, sharing lessons learned with the journalism community, and keeping technology in service of reader needs rather than the other way round. Human editorial control remains non-negotiable.

Questions

Editorial inquiries about AI usage: editorial@tickstock.io. For technical questions about the platform: platform@tickstock.io.