TextMark: AI Probability Inspector for publisher-grade authenticity signals
TextMark helps editorial teams evaluate long-form submissions using transparent statistics aligned with behaviors seen in SynthID-style token watermarking, so you can prioritize human review without guesswork.
Run the TextMark statistical inspection
Paste contributor copy below. TextMark computes entropy dispersion, word-length variance, and repetitive n-gram pressure, then maps those signals to a probability-style score calibrated for editorial triage.
Tip: longer samples usually stabilize the readout. Very short snippets can look noisy even when the writing is human.
Idle
Composite probability readout
Frequently asked questions
TextMark summarizes multiple statistical views of your passage, including character-level entropy, how tightly word lengths cluster, and whether short n-grams repeat in ways that often appear when token-level constraints influence phrasing. The result is a single probability-style score designed for triage, not a courtroom claim.
No. TextMark is an editorial instrument. It helps you decide which submissions deserve deeper verification, which freelancers need coaching, and how to document a reasonable review process. Always combine automated signals with policy, sourcing, and experienced editors.
The workflow on this page runs in your browser so you can iterate quickly during review. Treat it like any web form: do not paste regulated, confidential, or personally sensitive content unless your security team approves. If you need enterprise logging or retention controls, route analysis through your internal pipeline instead.
Why Use TextMark: AI Probability Inspector?
Speed
Editorial calendars punish delay. TextMark turns a long article into a compact statistical snapshot in seconds, so your team can route urgent pieces to the right reviewer, batch similar risk levels together, and keep production moving without sacrificing a structured checkpoint. The interface stays focused on one job: a clear readout you can act on immediately.
Security
Publisher workflows touch valuable intellectual property. TextMark is built around a local analysis demo mindset, reducing the impulse to send raw contributor drafts through opaque pipelines. Pair the tool with your internal data classification rules, redact identifiers when needed, and keep audit notes inside your CMS where they belong.
Quality
Quality is not a vibe check. TextMark explains its readout using measurable features like entropy and n-gram repetition so editors can compare revisions, study how coaching changes a freelancer’s fingerprint, and build consistent standards across desks. Over time, your newsroom learns what “normal” looks like for your vertical.
SEO
Search engines reward helpful, human-centered content, but scaling content programs invites mixed sourcing. TextMark gives SEO and editorial leads a shared language for risk: a score trendline across drafts, a sanity check before publishing a sensitive YMYL page, and a defensible reason to invest in expert review when statistics drift toward synthetic-looking regularity.
Who Is This For?
Bloggers
If you accept guest posts, you are one viral mistake away from a trust crisis. TextMark helps you screen submissions before they touch your template, compare suspicious paragraphs to your house style, and keep your personal brand aligned with authentic storytelling rather than templated fluency.
Developers
Engineering blogs and documentation programs often mix human experts with assistants. TextMark offers a quick statistical pass on README drafts, migration guides, and long troubleshooting articles so technical reviewers can focus on correctness while still catching passages that read overly smoothed or mechanically regular.
Digital marketers
Campaign landing pages and pillar posts must be compliant and credible. TextMark supports pre-publish QA when multiple vendors touch the same asset, helping you spot sections that may need a human rewrite, an expert quote, or a disclosure update before the page earns traffic.
The ultimate guide to TextMark for editorial teams
What TextMark is and what problem it targets
TextMark is a browser-based inspection workflow that treats long-form writing as data you can measure, not just prose you can skim. Modern publishers face a practical dilemma: production timelines are tight, contributor networks are global, and the incentives to cut corners are real. At the same time, audiences and platforms are asking harder questions about authenticity. TextMark does not pretend to read minds or identify authors. Instead, it focuses on a narrower and more actionable question for editors: does this passage exhibit statistical regularities that resemble the footprint of token-level constraints associated with SynthID-style watermarking patterns that sometimes appear in machine-influenced text?
That framing matters because it keeps expectations honest. Watermark-oriented signals are not a universal detector of creativity. Humans can write in highly regular ways, especially in regulated industries. Conversely, machine-assisted drafting can be heavily edited until it looks idiosyncratic. TextMark is therefore built as a triage layer. It helps you sort submissions into buckets: likely routine, worth a second read, or prioritize for deeper verification. When used consistently, it becomes part of a quality system rather than a single thumbs up or down.
Why this kind of inspection matters for publishers in 2026
Trust is an economic asset for publishers. When readers believe your byline means a human expert stood behind the claims, they subscribe, return, and share. When that trust erodes, the damage is rarely limited to one article. Editorial leaders therefore need tools that support transparency without turning every workflow into a forensic lab. Statistical inspection bridges that gap because it produces repeatable outputs. Two editors can run the same draft and discuss the same features: entropy, dispersion, repetition structure. That shared vocabulary reduces arguments rooted purely in intuition.
There is also a compliance angle emerging across regions and platforms. Even when the law does not mandate a specific tool, internal governance often does. Investors, partners, and advertisers increasingly ask how organizations manage generative risk. A documented step that includes measurement, human review, and escalation paths is easier to defend than a policy that lives only in a PDF. TextMark is not legal advice, but it gives teams a concrete checkpoint they can cite as part of due diligence.
Finally, watermark-oriented thinking aligns with how some modern systems embed signals in text generation pipelines. Whether or not a particular model exposes watermark metadata to you, the editorial task remains: identify passages that look mechanically constrained relative to your expectations. TextMark encodes that task into a practical interface so publishers can operationalize it at scale.
How to use TextMark effectively inside a real newsroom or content program
Start with baseline calibration using content you trust. Run several known-human pieces from your own archive through TextMark and note the typical ranges. Then run pieces you feel confident were heavily templated or machine smoothed. The goal is not to memorize a single threshold but to understand variance. Next, integrate TextMark at a predictable stage. Many teams get the best results when inspection happens after an initial copy edit but before final legal review, because the text is stable enough for statistics to mean something yet still early enough for rewrites.
When a score looks elevated, resist the urge to leap to accusations. Instead, compare alternative explanations. A financial explainer may score oddly because it repeats standardized definitions. A breaking news update may show repetition because it quotes the same official statement across paragraphs. A travel guide may show tight structure because the genre demands it. TextMark is most powerful when paired with prompts: ask the contributor for sourcing notes, compare against earlier assignments, or request a short rewrite of only the flagged section while preserving facts.
Document what you did. A lightweight note in your CMS or ticketing system can record the score, the features you saw, and the human decision. Over a quarter, those notes become training data for your editors, not for the model, but for your organization. You learn which freelancers benefit from coaching, which topics need specialist reviewers, and where your style guide should be clearer about acceptable assistance.
Common mistakes to avoid when interpreting statistical signals
The first mistake is treating any probability readout as proof. Probabilities in this context are editorial heuristics derived from text features, not courtroom exhibits. The second mistake is analyzing too little text. Short snippets amplify noise. If you must evaluate a short passage, compare it to adjacent paragraphs from the same document rather than relying on an absolute number alone. The third mistake is ignoring revision history. Machine-assisted first drafts that were deeply edited by a skilled human may present a different profile than a lightly edited draft.
The fourth mistake is using the tool inconsistently. If only some desks run checks, your standards drift and your freelancers get mixed signals. A better approach is to define simple rules: everything over a certain length gets a pass, everything from new contributors gets a pass for the first month, everything in sensitive categories gets a pass regardless. The fifth mistake is neglecting contributor relationships. Statistics can start conversations, but they should not replace respectful clarification. Many issues resolve with better briefs, clearer examples of tone, and explicit policies about disclosure.
Used with discipline, TextMark helps Text Marks readers feel the difference between content that is engineered for trust and content that merely looks polished on the surface. That difference shows up in retention, in fewer corrections after publication, and in a calmer newsroom that spends less time fighting fires and more time publishing work worth paying for.
How it works
1
Paste long-form text
Copy the contributor draft into the inspector and confirm you are following your internal confidentiality rules.
2
Normalize and tokenize
TextMark extracts words, computes character entropy, and measures how tightly lengths cluster across the passage.
3
Scan n-gram repetition
Short phrase repeats are compared against expectations for natural variation to estimate mechanical regularity pressure.
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Map signals to probability
Features blend into a composite readout with a meter and metric breakdown suited for editorial triage.
About Text Marks
Text Marks builds focused utilities for teams that publish under pressure and still want their pages to feel human. We care about clarity, measurable review steps, and tools that respect how editors actually work. Our roadmap starts with TextMark because watermark-aware statistics answer a timely question without turning every workflow into a black box.
We believe publishers should be able to explain their standards to contributors and readers alike. That is easier when your process includes transparent checks rather than secret vibes. If you want the longer version of our story, values, and commitments, use the button below.
Editorial intelligence articles
Practical guidance for teams using TextMark: AI Probability Inspector to evaluate long-form writing with statistical discipline.
What is TextMark: AI Probability Inspector and why every publisher needs it
A plain-language introduction to watermark-aware statistics for contributor workflows. Estimated read time: 11 minutes.
From gut feel to a repeatable checkpoint
Publishing organizations have always relied on experience. Senior editors develop an ear for tone, a nose for inconsistency, and a quiet suspicion when a paragraph sounds too frictionless. That intuition remains invaluable, but it does not scale cleanly across a global freelancer pool, a 24-hour news cycle, and an expanding set of verticals. TextMark exists to add a layer that scales: a structured inspection pass that highlights statistical features aligned with behaviors observed when token-level constraints influence phrasing, including patterns associated with SynthID-style watermarking discussions in the industry.
What the inspector actually computes
At a high level, TextMark summarizes three families of signals. First, it measures how information is distributed across characters, because overly uniform or oddly constrained distributions can appear when generation processes impose subtle regularities. Second, it examines word-length dispersion, since some drafting workflows produce clusters of similar-length tokens in ways that differ from many human first drafts. Third, it evaluates short n-gram repetition, because mechanical processes sometimes recycle phrasing patterns that humans would vary when writing for readers rather than for completion.
None of these features is a smoking gun in isolation. That is why TextMark presents a composite readout rather than a single binary flag. The goal is to give your desk a ranked sense of where to spend attention, not to automate moral judgment.
Why publishers are adopting triage tools now
The economic pressure to publish more content is not new, but the tooling available to contributors changed quickly. Even when policies prohibit undisclosed machine drafting, enforcement is uneven. Editors need methods that are fast enough for daily use and explainable enough to discuss with legal, HR, and external partners. TextMark fits that niche by producing metrics you can cite in notes, compare across revisions, and use to coach writers with specifics rather than vibes.
How TextMark supports trust without theatrics
Readers do not owe publishers infinite patience. When a story is wrong or misleading, the correction cycle is painful. TextMark reduces preventable surprises by encouraging a disciplined review step before publication. It also helps teams communicate standards internally. When everyone knows long features receive a statistical pass, freelancers understand expectations and quality becomes less personal and more procedural.
Putting TextMark into practice this quarter
Start with a pilot desk. Choose a content type with stable structure, such as explainers or product roundups. Run TextMark on a month of drafts and compare outcomes to your historical correction rate. Adjust thresholds based on your risk tolerance. Expand only after editors agree the workflow saves time rather than adding theater. If you want to run an inspection immediately, return to the home experience and open the tool section.
Deeper context for leadership and legal partners
Publishers increasingly answer questions about process, not only about outcomes. When a stakeholder asks how you know freelancers meet standards, a credible answer references concrete steps. TextMark contributes a measurable checkpoint that can sit alongside plagiarism scanning, fact checking, and disclosure policies. It does not replace those steps. It complements them by addressing a different failure mode: passages that may be factually plausible yet statistically reminiscent of token-level constraints seen in some machine-assisted drafting pipelines, including those discussed in connection with SynthID-style watermarking.
Leaders should also plan communication with contributors. Writers deserve clarity about what you test and why. A calm, procedural explanation reduces anxiety and reduces adversarial dynamics. Many freelancers welcome feedback that helps them align with a publication’s voice. TextMark metrics can guide coaching conversations with specificity, especially when editors compare an early draft to a revised draft and show how variance and repetition features changed after rewrite guidance.
Finally, consider archiving aggregated statistics rather than storing every score forever. Some teams keep monthly distributions only, which still supports trend analysis without retaining unnecessary detail. Align retention to your privacy policy and to regulations that apply to your operations. When in doubt, treat contributor drafts as sensitive business records and limit duplication across systems.
TextMark: AI Probability Inspector versus manual alternatives: which saves more time?
A realistic comparison of reviewer hours, consistency, and hidden costs. Estimated read time: 12 minutes.
The manual playbook still works, slowly
The traditional alternative to a tool like TextMark is a senior editor reading every line while mentally checking for tells: generic transitions, suspiciously even rhythm, factual blandness, or a mismatch between claims and voice. That method can be accurate when the editor is fresh, familiar with the beat, and not juggling Slack escalations. It fails when volume spikes, when the desk is short-staffed, or when the same editor must compare five submissions that all look competent on the surface.
Where manual review hides expensive rework
Manual review often discovers problems late. A problematic freelance feature may reach layout before anyone notices a subtle uniformity issue. Rework at that stage collides with ad operations, newsletter timing, and social promotion. Even when issues are caught earlier, manual review produces uneven documentation. One editor may flag a concern verbally while another fixes quietly. Without metrics, teams struggle to prove they applied consistent standards across months.
What TextMark adds in minutes per article
TextMark does not eliminate reading. It compresses the first-pass triage. Instead of wondering whether a passage deserves deeper scrutiny, you start with a structured hint. Editors still verify facts, check quotes, and evaluate argument quality. The difference is that attention becomes allocatable. High-risk drafts get more time, while straightforward pieces move faster. In programs measured by throughput, that reallocation shows up as fewer bottlenecks without lowering the bar on the pieces that matter most.
Consistency as a form of fairness
Manual alternatives can unintentionally bias toward writers who mimic a house voice or who have personal relationships with editors. A statistical pass is imperfect, but it is more uniform than mood. When combined with human judgment, it supports fairer freelancer programs because expectations are less dependent on which editor happened to pick up the ticket.
Choosing a hybrid workflow that respects humans
The best answer is rarely tool-only or human-only. Use TextMark at a defined stage, keep escalation paths for contested results, and train editors to interpret metrics with context. Measure outcomes quarterly. If the tool saves time and reduces post-publish fixes, keep it. If it creates noise, tighten policies around sample length and category rules. When you are ready to compare workflows on a real draft, jump to the inspector from the home view.
Time studies that match how desks actually behave
When teams estimate manual review time, they often imagine uninterrupted reading. Real newsrooms interrupt constantly. A twenty-minute article may consume far more than twenty minutes of calendar time once messaging, meetings, and production fixes are included. TextMark reduces the uncertainty in the first allocation decision: should this piece go to a senior editor now or can it follow the standard queue? That decision is small but repeated hundreds of times per month.
Manual review also creates hidden rework when two editors disagree without data. Debates drift into subjective territory. A metric does not end debate, but it anchors discussion. Editors can agree on what changed between revisions and whether coaching improved measurable variance. That alignment saves time emotionally and operationally, especially in remote teams where tone in chat can be misread.
Another cost of manual-only review is opportunity cost. Senior editors are scarce. If they spend hours on drafts that statistics suggest are routine, high-risk pieces wait. TextMark helps route scarce attention toward submissions that need expert judgment, which is the real time savings most organizations feel first.
How to use TextMark: AI Probability Inspector to improve your SEO in 2026
Align search strategy with authentic expertise signals using disciplined drafting review. Estimated read time: 12 minutes.
Why SEO teams should care about authenticity mechanics
Search engines continue to emphasize helpful content written for people. That guideline sounds simple until you operate a large site where dozens of writers produce similar pages. SEO leaders worry about duplicate patterns, thin expertise, and pages that read optimized but hollow. TextMark supports a different approach: treat authenticity as an engineering property you can observe, not only a brand promise you assert.
Using TextMark before internal linking and schema go live
Many SEO fixes happen after publication. That is expensive. A better sequence is to run TextMark on drafts while titles, headings, and FAQ modules are still flexible. If a passage shows elevated regularity, rewrite before you bake structured data around it. This reduces the risk of promoting content that later requires a heavy revision cycle.
Pair TextMark with expert review on YMYL topics
Your money, your life pages carry outsized risk. Statistical inspection does not replace medical, legal, or financial review, but it can help SEO and editorial teams agree on which drafts need specialist attention first. When TextMark highlights repetitive scaffolding, experts spend less time fighting generic phrasing and more time validating claims.
Measuring improvement across content sprints
SEO programs often run quarterly sprints. Track distributions of TextMark readouts over time, alongside human ratings of satisfaction. If coaching works, you should see fewer extreme scores and more stable variance, reflecting writers who internalize tone and structure. If scores remain flat, your briefs may be too templated, pushing humans toward mechanical patterns unintentionally.
A practical weekly cadence for hybrid teams
On Monday, sample ten upcoming URLs. Run TextMark on each draft body. Share anonymized learnings in a short standup. On Wednesday, focus on pages targeting competitive keywords. On Friday, review anything that changed hands between agencies. This cadence keeps SEO, editorial, and compliance aligned without turning every task into a committee. Start a pass now from the home tool section.
Connecting E-E-A-T signals to measurable drafting habits
Experience, expertise, authoritativeness, and trustworthiness are not single metrics, yet they still depend on concrete page qualities: specific examples, accountable claims, and a voice that sounds grounded in practice. TextMark does not score E-E-A-T directly. It helps teams detect drafting habits that often correlate with generic smoothing, which can undermine perceived expertise even when keywords are present.
Consider a long guide that repeats the same transition phrases and symmetrical sentence shapes. Readers may not articulate why it feels shallow, but they bounce. Search systems increasingly reflect user satisfaction signals. TextMark gives SEO teams an early warning when a draft’s statistical regularity suggests templated composition, prompting editors to add firsthand detail, named sources, and section-level variation.
For international SEO programs, combine TextMark with localization review. Sometimes translation memory creates repetitive scaffolding that resembles machine-like uniformity even when the source was human. A statistical pass helps prioritize human polish for locales that matter most commercially, which is a smarter use of limited localization hours than spreading effort evenly across pages that do not need it.
Top five use cases for TextMark: AI Probability Inspector you have not thought of
Unusual but high-value places to deploy watermark-aware statistics beyond obvious newsroom triage. Estimated read time: 11 minutes.
Vendor onboarding for white-label content programs
Agencies frequently inherit writers they did not train. A two-week onboarding window can include TextMark sampling across assignments. You learn whether a vendor’s baseline voice matches your risk tolerance before you grant access to premium clients.
Litigation-adjacent documentation where process matters
Some teams must show they took reasonable steps even when no single tool is definitive. A logged review habit that includes statistical inspection plus human notes can be part of a defensible record. Always coordinate with counsel for your jurisdiction.
Education partners and university newsrooms
Student publications balance teaching with credibility. TextMark can be used as a teaching aid: students see how revision changes measurable features, connecting grammar instruction to real outcomes.
Localization QA when translation memory dominates
Localized pages sometimes inherit repetitive scaffolding from translation workflows. TextMark can flag when English source patterns survived too literally, helping localization leads prioritize human polish for high-traffic locales.
Investor and public relations materials
External communications demand accuracy and tone discipline. Before releasing lengthy letters or FAQs, a quick statistical pass can catch sections that read overly smoothed, prompting executives to add specifics only humans know.
Make your next unexpected use case deliberate
The pattern across these examples is simple: wherever long-form text represents reputational risk, a fast inspection layer helps. Return to the home page tool section to test a sample from your next unconventional project.
Operational patterns that make rare use cases reliable
Uncommon workflows fail when they depend on heroics. If only one person remembers to run checks before a board meeting, the process is fragile. TextMark becomes durable when it is embedded in templates: a checklist item in your CMS workflow, a required field in your ticketing system, or a scheduled reminder for recurring publications such as quarterly investor letters.
Another pattern is pairing TextMark with version control for prose. Teams that draft in repositories or collaborative documents can compare statistical profiles across commits. That comparison helps writers see how edits change measurable features, reinforcing good habits without turning writing into a game of chasing numbers.
Finally, unusual use cases often involve cross-functional trust. Legal may worry about claims, marketing may worry about tone, and product may worry about accuracy. A shared inspection step creates a neutral artifact everyone can look at together. The score is not a verdict, but it is a focal point for discussion, much like a lighthouse report for web performance.
Common mistakes when checking contributor drafts for machine influence, and how TextMark fixes them
Avoid false confidence, false alarms, and policy gaps with a structured approach. Estimated read time: 12 minutes.
Mistake one: judging from a tiny excerpt
Editors sometimes paste two paragraphs and expect certainty. Short samples amplify noise. TextMark works best with longer passages because entropy and n-gram measures stabilize. If you only have a short quote, compare it to the full document rather than isolating it.
Mistake two: treating a score as an accusation
A high readout is not a verdict. It is a prompt to review. TextMark encourages procedural calm: verify sourcing, compare to prior work, and request clarification when appropriate. Many situations resolve with better briefs and disclosure rather than conflict.
Mistake three: skipping policy alignment
Tools amplify whatever policy you already have. If your organization has not defined acceptable assistance, editors improvise and freelancers get mixed messages. TextMark fits cleanly when leadership publishes clear guidance about disclosure, originality expectations, and review stages.
Mistake four: ignoring genre effects
Regulated explainers, listicles, and narrative features behave differently. A score without context misleads. TextMark performs best when editors categorize the draft and interpret metrics with genre in mind, rather than applying one universal threshold.
Mistake five: failing to document outcomes
Teams that do not record decisions learn slowly. Capture the score, the action taken, and the result. TextMark becomes more valuable when it feeds a learning loop, not when it becomes a one-off curiosity.
How TextMark reinforces better habits
By making signals explicit, TextMark nudges teams toward longer samples, calmer escalations, clearer policies, genre awareness, and documentation. That combination reduces mistakes more than any single number could. Run your next check from the home tool area.
Building a learning loop that compounds
Mistakes become expensive when organizations do not learn from them. A postmortem that ends with vague guidance rarely changes behavior. TextMark supports learning loops because it produces comparable artifacts across incidents. When a correction happens, teams can record what the metrics showed beforehand, what editors suspected, and what policy changed afterward. Over time, patterns emerge: certain topics, certain vendors, certain briefing formats.
Training benefits too. New editors often fear false accusations. A tool framed as triage reduces that fear because the workflow emphasizes verification and coaching. Veterans can mentor juniors using concrete examples: here is a draft with elevated repetition pressure, here is how we requested sourcing, here is the revised draft’s improved variance. That mentorship is easier when the organization treats statistics as part of craft rather than as surveillance.
Externally, transparency can be a competitive advantage. Some publishers publish methodology summaries describing how they review submissions. You need not share proprietary thresholds to explain that you combine human editing with statistical checks aimed at detecting unnatural regularities. Readers increasingly appreciate honesty about process, especially in an era of synthetic media anxiety.
About Text Marks
Our mission
Text Marks exists to help publishing teams protect reader trust without pretending complexity can disappear. We believe the best editorial operations combine human judgment with transparent processes that scale. Our mission is to ship focused tools that respect your time, explain their outputs in plain language, and fit naturally between drafting, editing, and compliance review.
We are motivated by a simple observation: the internet rewards speed, but audiences remember quality. Organizations that try to win on volume alone often discover that short-term metrics rise while long-term reputation decays. Text Marks aims to bend that curve back toward sustainable publishing by giving teams practical measurement layers that make good standards easier to follow than to skip.
We also care about accessibility of good practice. Smaller publishers deserve workflows that do not require enterprise budgets to implement. That is why Text Marks emphasizes clear interfaces, local analysis where possible, and documentation that helps non-technical editors understand what a score means and what it does not mean.
What we build
Our flagship experience on this site is TextMark: AI Probability Inspector, a workflow for inspecting long-form text using statistical features associated with SynthID-style token watermark patterns. It is designed for editors, program managers, and operations leads who need a fast triage signal before investing deeper review time.
TextMark is not a universal authenticity oracle. It is a disciplined first pass. It helps teams sort drafts, coach contributors with specifics, and document that a reasonable check occurred. We build for newsrooms, independent blogs, developer education programs, and marketing organizations that publish long articles under real-world constraints.
Our values
Privacy
We treat publisher content as sensitive by default. The demo workflow on this page is engineered to analyze text locally in your browser so you can iterate quickly without an account. We still urge every organization to follow its own data classification rules. Privacy is not only a technical setting; it is a habit. We encourage teams to avoid pasting regulated data into any web form and to route highly sensitive material through internal systems approved by security stakeholders.
Speed
A tool that slows publishing will be abandoned, no matter how clever it is. We optimize for a fast path from paste to readout, with readable metrics that help editors decide next steps immediately. Speed also means respectful performance on common hardware and mobile widths, because review happens on laptops, tablets, and phones in the field.
Quality
Quality is an outcome of repeatable standards. Text Marks focuses on outputs that teams can compare across time: scores, metric breakdowns, and consistent terminology. We avoid hype language that promises certainty science cannot support. Instead, we aim for clarity and usefulness under real editorial pressure.
Accessibility
Publishing tools should be usable by busy people with diverse roles. We prioritize legible typography, sufficient contrast, large touch targets, and navigation that works with keyboards and screen readers in mind. Accessibility is both an ethical commitment and a practical one: inclusive design reduces mistakes and training time.
Our commitment to free tools
Text Marks is committed to keeping core inspection utilities free at the point of use on the web so smaller teams can adopt good practices without procurement friction. Free access does not mean free responsibility: we still encourage organizations to integrate policies, training, and human review. If we introduce optional paid features in the future, we will aim to preserve a meaningful free tier that supports independent publishers and educators.
Contact and feedback
We improve TextMark based on real editorial feedback. If you have workflow suggestions, bug reports, or partnership questions, email haithemhamtinee@gmail.com. Please include enough context that we can reproduce issues, such as browser version, sample length, and what you expected the readout to do.
How we think about responsible publishing
Responsible publishing is not a single tool purchase. It is a culture of verification, transparency with readers, and fair treatment of contributors. Text Marks tries to reduce the gap between aspiration and daily practice by making one important checkpoint lightweight enough to use consistently. We know publishers face economic pressure; we also know trust compounds slowly and erodes quickly.
We welcome critique from journalists, librarians, educators, and civil society researchers who study information integrity. If you believe we should adjust our language to avoid overstating capabilities, we want to hear that feedback. Precision matters in a space crowded with hype.
Looking forward, Text Marks may expand into additional utilities that support editorial operations, always with the same design principles: privacy-aware defaults, fast workflows, honest limitations, and accessibility for smaller teams that cannot afford enterprise suites.
Contact Text Marks
We welcome messages from editors, publishers, educators, and partners who want to improve how long-form content is reviewed. Use the information below to reach the Text Marks team for support requests, product feedback, and business conversations.
We typically respond within 24–48 hours on business days. Complex investigations may take longer, but we will acknowledge receipt as soon as we can.
What to include in your message
Please include a clear subject line, a short description of your request, and steps to reproduce any issue you encountered. If your report involves display problems, attach a screenshot when possible and mention your browser and device. Avoid sending confidential drafts unless you have approval to share them.
Business inquiries versus support requests
Support requests include questions about using TextMark, interpreting readouts, or reporting unexpected behavior. Business inquiries include partnership proposals, licensing discussions, custom integrations, and media requests. You may use the same email for both; just label the subject line accordingly so we can route your message efficiently.
Privacy when you contact us
Email is a normal channel for support, but it is not a secure vault. Do not include passwords, payment card numbers, or highly sensitive personal data. If you need to share sensitive material under NDA, state that explicitly so we can coordinate an appropriate channel with your team.
Privacy Policy
Last updated:
Introduction and who we are
This Privacy Policy explains how Text Marks approaches information practices in connection with the TextMark: AI Probability Inspector experience hosted at this domain. Text Marks provides a web-based utility intended to help publishers inspect long-form text using statistical methods. We describe our practices in plain language while acknowledging that your organization may impose additional requirements.
Depending on how you use the site, different data flows may apply. Some interactions may occur entirely in your browser, while others may involve standard web infrastructure such as hosting logs. This policy is designed to help you make informed decisions.
Text Marks recognizes that publishers operate under varied regulatory environments. Nothing in this policy overrides stricter obligations you may have under employment agreements, union rules, sector-specific laws, or contracts with contributors. If you process personal data subject to GDPR, UK GDPR, CCPA, or similar frameworks, treat this document as a baseline disclosure and supplement it with your own records of processing activities where required.
We may update our infrastructure, analytics configuration, or advertising partners over time. When we do, we will adjust this policy to remain accurate. Your continued use after updates means you acknowledge the revised description, except where applicable law requires a different consent mechanism for material changes.
What data we collect
Inputs you provide. When you paste text into TextMark, that content is processed to produce the on-page analysis. In the demo workflow emphasized on this site, processing is intended to occur locally in your browser. You should still treat pasted text as sensitive and avoid submitting regulated or confidential information unless permitted.
Usage data. Like most websites, our hosting environment may automatically collect technical information such as IP address, user agent, timestamps, and request paths. This data helps maintain security and diagnose outages.
Cookies and similar technologies. We may use cookies or local storage for essential site functionality, analytics, or advertising, as described further below and in our Cookies Policy.
Communications. If you email us, we receive your message content, email address, and metadata associated with the transmission.
How we use your data
We use information to operate and improve the site, respond to support requests, secure our infrastructure, comply with law where applicable, and understand aggregated usage patterns. We do not sell personal information as a business model. If we use analytics or advertising services, those vendors may process information under their own policies.
Operational uses include detecting abuse, preventing fraud, measuring reliability, and troubleshooting errors. Improvement uses may include understanding which pages are visited most often and whether features appear to load successfully across regions. Support uses include responding to emails and maintaining correspondence records long enough to resolve issues unless a longer retention period is legally required.
Where feasible, we prefer aggregated or de-identified reporting for analytics. Aggregation does not eliminate all privacy risk, especially when datasets are small or unique visitors are identifiable by rare attributes. We encourage visitors to use browser controls, VPNs where appropriate, and organizational policies that limit pasting sensitive content into web forms.
Cookies and tracking technologies
We may use cookies to remember preferences, measure performance, or support advertising. You can control many cookies through browser settings. Additional detail appears in our Cookies Policy, including categories such as essential, analytics, and advertising cookies.
Third-party services
This site may incorporate third-party technologies, including Google Analytics for aggregated traffic measurement and Google AdSense for advertising delivery where enabled. Those services may collect device and usage information according to Google’s policies. We encourage you to review Google’s privacy documentation and use opt-out tools where available.
Your rights under GDPR
If GDPR applies to you, you may have rights to access, rectify, erase, restrict processing, object, and request data portability regarding personal data we control. You may also lodge a complaint with a supervisory authority. To exercise rights, contact us using the email below. We may need to verify your request.
Data retention
Retention depends on the data category. Server logs may be retained for a limited period for security. Support emails may be retained as needed to resolve issues and maintain records. Analytics data may be retained according to vendor settings. We aim to keep retention no longer than necessary for legitimate purposes.
Browser-local processing may leave fewer server-side traces, but browsers can still store cached assets, service worker state, or other artifacts depending on your configuration. Clearing site data can remove many local traces, though backups and logs outside the browser may still exist if you transmitted data over the network.
If we receive a legal request for information, we may retain certain records longer than ordinary business needs require, consistent with legal obligations and internal legal hold procedures. We will scrutinize requests and respond only as permitted by law.
Children’s privacy
Text Marks does not knowingly collect personal information from children under 13. If you believe a child provided information, contact us and we will take appropriate steps to delete it where required.
Changes to this policy
We may update this Privacy Policy to reflect operational, legal, or technical changes. We will revise the last updated date and post the updated policy on this page.
By accessing or using the Text Marks website and TextMark: AI Probability Inspector tools provided through it, you agree to these Terms of Service. If you do not agree, do not use the site. If you use the site on behalf of an organization, you represent that you have authority to bind that organization to these terms.
These terms form a binding agreement between you and Text Marks regarding use of the public web experience. Some jurisdictions limit certain disclaimers or liability caps for consumers. If you are a consumer, mandatory rights may apply despite language below.
If you access the site from a country with local law requirements for online contracts, you are responsible for compliance with those laws in addition to these terms. Where local law conflicts with a provision and invalidates it, the remaining provisions remain enforceable to the maximum extent permitted.
Description of service
Text Marks provides an online utility that analyzes pasted long-form text and presents statistical readouts intended for editorial triage. Outputs are informational and may be incomplete or incorrect. The service may change, pause, or discontinue at any time.
Permitted use and restrictions
You may use the service for lawful purposes only. You agree not to misuse the site, attempt unauthorized access, interfere with security, scrape in a way that harms performance, or use the service to violate others’ rights. You are responsible for the content you paste and for complying with your employer’s policies and applicable law.
Intellectual property
The site design, branding, text, and underlying code are owned by Text Marks or its licensors and are protected by intellectual property laws. You receive a limited, non-exclusive license to use the site for its intended purpose. You may not copy, modify, or reverse engineer except as permitted by law.
Disclaimers and no warranties
The service is provided “as is” without warranties of any kind, express or implied, including merchantability, fitness for a particular purpose, and non-infringement. TextMark outputs are not guarantees about authorship, originality, or suitability for any decision.
Limitation of liability
To the fullest extent permitted by law, Text Marks will not be liable for indirect, incidental, special, consequential, or punitive damages, or for loss of profits, data, or goodwill. Our aggregate liability arising out of these terms or the service will not exceed the greater of zero dollars or the minimum amount enforceable under applicable law.
Because the service is provided without charge in its public form, many jurisdictions permit broader limitation of liability than in paid enterprise agreements. If you rely on TextMark outputs for high-stakes decisions, you accept that risk. Insurance, contractual indemnities, and internal review processes remain your responsibility.
Some regions do not allow exclusion of certain warranties or limitation of liability for gross negligence or willful misconduct. Nothing here limits liability that cannot legally be limited.
Cookie notice and GDPR compliance
Our cookie practices and GDPR-related disclosures are described in our Privacy Policy and Cookies Policy. Where consent is required, we aim to provide clear choices consistent with applicable regulations.
Links to third-party sites
The site may reference or display third-party resources. We are not responsible for third-party content, policies, or practices. Your use of third-party services is at your own risk.
Modifications to the service
We may modify features, impose limits, or discontinue portions of the service. We may update these terms by posting a revised version on this page. Continued use after updates constitutes acceptance unless applicable law requires additional steps.
Governing law
These terms are governed by applicable law without regard to conflict-of-law principles that would require applying another jurisdiction’s laws, except where prohibited. Courts in the appropriate venue may have exclusive jurisdiction, subject to mandatory consumer protections.
Cookies are small text files stored on your device when you visit a website. They help sites remember settings, measure usage, and support advertising. Cookies can be first-party or third-party, session or persistent, depending on how long they remain and who sets them.
Similar technologies include local storage, session storage, pixels, and software development kits embedded in advertising or analytics stacks. These technologies can recognize returning browsers, measure conversions, or personalize experiences. They vary in persistence and in whether they transmit data to third parties.
Users can often delete stored data through browser settings. Deletion may log you out of services, reset preferences, or reduce convenience features. Some technologies may repopulate after the next visit if the site sets them again.
How we use cookies
Text Marks may use cookies and similar technologies to enable core functionality, analyze traffic patterns, and support advertising where implemented. The goal is to keep the site reliable while understanding how visitors use features responsibly.
Types of cookies we use
Cookie name
Type
Purpose
Duration
tm_essential
Essential
Stores basic UI preferences needed for navigation and consent state where applicable.
Session to 12 months
tm_analytics
Analytics (Google Analytics)
Helps measure aggregated page views and feature usage to improve performance.
Up to 24 months per Google settings
_ga
Analytics (Google Analytics)
Google Analytics identifier used to distinguish users in aggregated reporting.
Up to 24 months
_gid
Analytics (Google Analytics)
Google Analytics session grouping helper for daily aggregation.
Typically 24 hours
adsense_prefs
Advertising (Google AdSense)
Supports ad delivery, frequency management, and fraud prevention where ads are enabled.
Varies by Google policies
NID
Advertising (Google)
Google advertising cookie that may be used for ad personalization and measurement.
Varies
Third-party cookies
Third-party cookies may be set by analytics or advertising providers such as Google when those services are enabled. Those providers have their own privacy policies and controls. We encourage you to review Google’s materials and use industry opt-out tools if you choose.
How to control cookies
Google Chrome
Open Settings, choose Privacy and security, then Cookies and other site data. You can block third-party cookies, clear existing cookies, or allow exceptions for specific sites.
Mozilla Firefox
Open Settings, select Privacy and Security, then choose your preferred cookie policy. Firefox provides enhanced tracking protection options and storage cleanup tools.
Safari
Open Preferences, select Privacy, then manage cookies and website data. Safari includes features designed to limit cross-site tracking.
Microsoft Edge
Open Settings, select Cookies and site permissions, then adjust tracking prevention and cookie blocking according to your preferences.
Cookie consent
Where required, we aim to obtain consent before using non-essential cookies. You may withdraw consent by clearing cookies and adjusting browser settings, subject to limitations of certain technologies.
Consent banners, when present, should describe categories clearly. Essential cookies may load without consent because they are necessary for basic site delivery. Analytics and advertising cookies often require consent under ePrivacy-style rules in certain regions. If you refuse non-essential cookies, some features may degrade, and some measurement may be incomplete.
Organizations using TextMark in professional contexts should coordinate cookie practices with their own privacy office. Enterprise environments sometimes block third-party cookies entirely, which can affect analytics accuracy but may improve privacy posture.