Editorial Policy & Research Methodology

This document explains how GrackerAI produces editorial content, including our research, fact-checking, sourcing, and update standards. It applies to every article, guide, glossary entry, comparison page, case study, and research report published on gracker.ai.

1. Who writes for GrackerAI

Editorial content is written or reviewed by GrackerAI staff with direct domain expertise. Bylines name the actual author and link to a full author profile that lists their role, prior work, and external profiles (LinkedIn, X, GitHub where applicable).

• Deepak Gupta — Co-founder & CEO. Background: serial entrepreneur, founder of LoginRadius (scaled to 1B+ users), 5 patents in identity and security.
• Govind Kumar — Co-founder & CPO. Background: AI architect and product engineer for identity, security, and developer infrastructure.

Guest contributions are clearly labelled and held to the same sourcing and disclosure standards as staff-written content.

2. Research methodology

GrackerAI research reports and benchmark posts follow a documented methodology:

• Source of truth. AI visibility metrics come from the GrackerAI platform, which polls ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, Gemini, Claude, Microsoft Copilot, DeepSeek, Meta Llama, and Grok daily (hourly on Enterprise).
• Sampling. Reports state the prompt set, the engines included, the time window, and the number of brands or prompts measured. We do not cherry-pick prompts.
• Reproducibility. Where prompts are public, we publish them. Where they are partner-proprietary, we name the partner and the prompt category.
• Statistical claims. Percentage changes and growth claims state the baseline, the time window, and the cohort size (e.g. "n = 87 customers, Q3 2025 vs Q1 2025").
• Independent verification. Customer-reported numbers used in case studies are reviewed with the customer prior to publication and sourced from the customer's own analytics, AI visibility dashboards, or CRM.

3. Citation and sourcing standards

• Factual claims link to a primary source whenever one exists. We prefer original research, vendor documentation, regulatory filings, peer-reviewed work, and reputable journalism — in that order.
• Numerical claims that come from our own data are labelled "GrackerAI internal benchmark" with the year and cohort.
• Numerical claims sourced from third parties are linked to the original report, not to a secondary aggregator.
• AI-generated content is reviewed and edited by a human before publication. Pages produced entirely by an LLM without human review are not published.
• We never use unverified screenshots, fabricated quotes, or invented statistics. If a claim cannot be sourced, we either remove it or rephrase it to make the uncertainty explicit.

4. Freshness and update cadence

• Every editorial page carries a datePublished and dateModified in its JSON-LD, and a visible "Last reviewed" line on flagship guides.
• Flagship guides (GEO/AEO concept pages, glossary, comparison pages, research reports) are reviewed at least every 6 months and on every major change to the underlying AI engines.
• Time-sensitive claims (model versions, pricing, feature availability) are reviewed quarterly.
• When we substantively change a page, we update dateModified and note the change in a brief update log near the top where it is material to readers.

5. Conflict of interest & disclosure

• GrackerAI is a commercial GEO/AEO platform. Where our editorial content discusses our own category, we say so explicitly.
• Comparison pages name competitors directly and link to their sites. We do not pay for placement and we do not accept payment for inclusion or removal.
• Customer case studies clearly identify the customer and state that the customer is a GrackerAI customer.
• If a GrackerAI author has a personal stake (advisory role, investment) in a product mentioned, that interest is disclosed inline.

6. AI and generative content policy

• We use AI tools to assist with research, drafting, and proofreading.
• A named human editor is responsible for every published page. The byline names that human, not the model.
• We do not use AI to fabricate quotes, statistics, sources, or customer outcomes. Anything attributed to a named person, customer, or external source is sourced and verifiable.

7. Corrections

If you find an error in our content — a factual mistake, an outdated number, a broken citation, a misquoted source — please email [email protected]. We will investigate within 5 business days. Substantive corrections are noted in an update line at the top of the page and the dateModified is updated.

8. Privacy & ethics

We follow our privacy policy in all editorial work, including how we handle customer data, prompt data, and any personally identifiable information that appears in research samples. We do not publish identifying details about individual end-users of monitored brands.

9. Contact

Editorial questions: [email protected]
Press & analyst inquiries: press page
Security disclosures: security page