AI Disclosure

Leading Through Transparency

Tickstock operates at the leading edge of journalism, automation and content production technologies.

As one of the small number of news operations openly building on AI-powered automation in financial coverage, we have an obligation to set a clear standard for responsible AI use.

The TickStock Newsroom Pipeline

What the Pipeline Is

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.

Why We Built This

Comprehensive coverage of fast-moving market sectors at a quality standard retail investors deserve requires more sustained editorial capacity than any small team can supply by hand, and would cost more than any independent publisher could economically stomach. Our technologies allow Tickstock a breadth of coverage without comprising quality, or being limited by commercially-driven curation.

Our technology allows us to augment human judgment with automation. Our machines handle volume and speed, whilst our humans handle nuance, judgment, and accountability.

Content Production: The Complete Picture

Step 1: Source Material Selection

Agentic and deterministic intelligence systems monitor news discovery vectors to identify newsworthy story candidates based on topic relevance, source credibility, and timeliness.

This work includes verification, semantic and contextual analysis against a broad and relevant scope of potential source material, including regulatory and corporate news announcements, market data, market and PR communications, and the outside news ecosystem.

Step 2: AI Drafting

Verified and relevant material goes to a drafting layer, plus a stringent post generation quality control system that prioritises:

• Factual accuracy and preservation of source claims
• Clear attribution of any claim that doesn't come from primary documents
• Removal of opinion unless attributed to a named source
• Plain language without sacrificing technical precision on tickers, financial figures, or regulatory specifics
• Contextual fact verification against proprietary knowledge and intelligence graphs

Step 3: Quality Control

Every drafted article passes through a robust quality control architecture before out human editors ever touch it. Pass 1 is editorial: does the article stand up as a piece of journalism? Pass 2 is verification and validation: Is the content supported by the source material and what we aleady know about this subject? Unsupported or ambiguous claims are flagged for human review and investigation

The platform rejects any and all fabricated quotes, fabricated figures, and claims that don't trace to source material or other qualifiying knowledge. More information about how we handle quality control can be found on our fact-checking page.

Step 4: Human Review

All content production is observable and supervised. We operate a human-centred, editor-in-the-loop methodology. There's is persistent human editorial monitoring of the platform as it runs, all activity and provenance is tracked and traced, and our systems operations include regular review and incremental development.

Crucially, every item of published content is authored by skilled and experienced human editors. Editorial accountability sits with the founder/publisher.

Step 5: Publication

Every published piece is the product of a human editor-in-the-loop system. AI-assisted articles carry the TickStock Newsroom collective byline, with full and detailed disclosures on every article, pointing back to this page.

What Gets the Newsroom Treatment, and What Doesn't

AI-Assisted Newsroom Coverage

The Newsroom pipeline is suited to:

• Structured news events of factual corporate developments
• Earnings releases and trading updates
• Director dealings, share buybacks, dividend announcements
• Capital raises, placings, and equity issuance
• M&A announcements (offers, defences, completions)
• Regulatory developments and policy changes affecting listed companies
• Sector and market updates drawn from structured data
• Broker note summaries with proper attribution

Human-Authored Content

The following stay with named human authors:

• Original investigative reporting
• Opinion and editorial commentary
• Analysis requiring expert judgment beyond the structured layer
• Interviews and first-person reporting
• Coverage of controversial or contested issues
• Corrections and clarifications
• Reader responses and engagement

What AI Does Not Do

AI in the TickStock pipeline does not:

• Make investment recommendations. No buy, sell, or hold calls. No price-target speculation outside attributed broker context.
• Decide what's newsworthy without human oversight. The pipeline surfaces candidates; editorial choices about coverage priorities sit with humans.
• Generate opinion or commentary as the publication's view. Opinion content is human-authored and clearly attributed.
• Publish content without source attribution. Every article ties back to identifiable and traceable underlying source inputs.
• Replace human judgment on matters of newsworthiness, fairness, accuracy, or fitness for publication.

Bias, Drift, and Where Humans Step In

Language Neutrality

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

Monitoring for Drift

To maintain the integrity of the platform, we undertake the following:

• Continuous audits of generated content for tone, accuracy, and source coverage
• Source diversity analysis to keep input balanced
• Reader feedback evaluation for perceived bias
• Continuous refinement of drafting parameters

Human Intervention Points

Every piece of content is authored and edited by experienced human editors. When underlying AI output exhibits any potential issues, upon review and escalation, we endeavour to adjust parameters where systematic patterns emerge, meanwhile at the specific content level, we manually edit problematic content and add context where appropriate.

Internally, human editors are empowered to flag issues for system review and improvement.

Coverage of AI Companies and Technology Providers

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 technology vendors
• Coverage of vendors follows identical standards as any other listed company
• Critical coverage proceeds without vendor consultation
• Disclosures are included when editorially relevant
• Competitor coverage proceeds without bias

Data and Reader Information

What We Collect

Tickstock collects minimal user data: standard web analytics (page views, traffic sources, location data at country level), email addresses (only if users volunteer them for specific reasons - for example, registration on the app waitlist), and engagement metrics on social channels.

What We Don't Do With Your Data

Tickstock does not use reader data to train AI models, sell user information to third parties, use reading patterns to manipulate content, or share data with AI providers beyond operational necessity.

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 this page if that changes.

Why a Collective Byline on AI-Assisted Content

AI-assisted Newsroom articles carry the Tickstock Newsroom byline rather than an individual author and editor's name. This is deliberate. Naming a single human author on a piece produced through a multi-stage AI-powered platform overstates that human's role and understates the institutional production process. The collective byline is honest about how the article was made.

Editorial accountability is concentrated at the founder/publisher level (as detailed via the About page), and the named contributing editorial team contributes to standards, commissioning, and individual bylined columns. Where a specific human edited or reviewed an AI-assisted article, that human is recorded within the platform, represented in the article metadata and is not asserted formulaically across the publication.

Future Evolution

AI technology evolves quickly. TickStock commits to:

• Disclose major platform changes to readers
• Evaluate new AI capabilities against journalism standards before adopting
• Share lessons learned with the journalism community
• Keep technology in service of reader needs, not the other way round
• Maintain human editorial control as a non-negotiable

Questions and Concerns

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