Quickly check whether an image may be AI-generated, manipulated, or authentic with i10X’s image analysis agent—built for fast verification, content review, and misinformation checks.
Juggling three image detectors caused daily fatigue and delays; i10X unified detection and cut our verification time 70%, speeding trusted publishes.
Verification Time Cut70%
Alex Rivera
Senior Editor
Our multi-tool stack burned $400 monthly plus switch time; i10X's free detector dropped costs 80% while tripling authenticity checks on product photos.
Tool Stack Cost Saved80%
Jordan Hale
Marketing Director
Spotting AI fakes across tools wasted hours on submissions; i10X delivers instant scores, saving our team 15 hours weekly on academic reviews.
Weekly Hours Saved15 hrs
Sam Patel
Digital Literacy Coordinator
Что агент может сделать для категории «Обнаружение и противодействие ИИ»
Один Superagent и специализированные субагенты для каждой задачи.
You upload an image or URL; i10X prepares it for secure authenticity analysis.
2
Set Detection Goals
You choose quick scan, batch review, or report depth; i10X configures the right checks.
3
Run Forensic Analysis
You start the scan; i10X inspects pixels, metadata, artifacts, watermarks, and AI fingerprints.
4
Review And Verify
You review confidence scores and guidance; i10X suggests next checks to reduce false positives.
Кому это подходит
Создано под конкретные задачи, которые люди решают каждый день.
Journalist / News Reporter
Задачи, которые берёт на себя агент
Upload or link source images for authenticity checks before publication.
Review AI-likelihood scores, metadata signals, and suspicious visual artifacts.
Compare image results with reverse search, source notes, and verification records.
Draft verification summaries for editors, legal teams, or publishing notes.
Результат: Deadlines stop being consumed by pixel-by-pixel doubt; reporters publish with faster visual confidence and cleaner editorial trails.
Fact-Checker
Задачи, которые берёт на себя агент
Batch-check viral images, claims, screenshots, and submitted evidence.
Flag manipulated or synthetic visuals for deeper investigation.
Document confidence scores, detector limitations, and supporting forensic observations.
Prepare clear verdict notes that separate likely real, likely synthetic, and inconclusive cases.
Результат: Suspicious images move from hunch to evidence-backed assessment, giving fact-checkers more time for context, sourcing, and public explanation.
Social Media Manager
Задачи, которые берёт на себя агент
Screen user-generated images before reposting, boosting, or approving campaigns.
Check viral visuals for synthetic or manipulated content before brand engagement.
Create quick authenticity notes for community, PR, and crisis-response teams.
Monitor repeated suspicious image patterns across social channels.
Результат: Brand teams can react to trends without gambling on fake visuals, keeping feeds faster, safer, and more credible.
Trust & Safety Moderator
Задачи, которые берёт на себя агент
Triage reported images for AI generation, manipulation, deepfake risk, or policy violations.
Prioritize high-risk visual content for human review using confidence signals.
Attach detector findings to moderation queues and enforcement decisions.
Spot repeat upload patterns that suggest coordinated misinformation or abuse.
Результат: Moderation queues become easier to prioritize, so reviewers spend less time guessing and more time acting on the riskiest content.
E-commerce Marketplace Manager
Задачи, которые берёт на себя агент
Verify seller-uploaded product images for AI-generated, counterfeit, or misleading visuals.
Flag listings with suspicious backgrounds, textures, logos, or edited product details.
Summarize image authenticity risk for catalog, compliance, and seller-quality teams.
Run recurring checks across large batches of marketplace images.
Результат: Catalog reviews shift from manual spot-checking to scalable visual risk screening, helping marketplaces protect buyers and seller trust.
Academic Integrity Officer
Задачи, которые берёт на себя агент
Review student-submitted artwork, visual assignments, and research images for AI-generation indicators.
Collect image analysis evidence for academic integrity case files.
Differentiate legitimate editing from likely synthetic or undisclosed AI-created work.
Prepare concise reports for faculty committees, students, and appeals processes.
Результат: Academic review becomes less adversarial and more evidence-led, freeing integrity teams to focus on fair decisions instead of manual forensics.
Superagent против отдельных инструментов
Возможность
Superagent
Отдельные инструменты
Setup and workflow launch
Configure an AI image authenticity workflow once, then reuse it across uploads, URLs, metadata checks, and review steps.
Each detector, reverse-image search, metadata viewer, and reporting template usually needs separate setup.
Tools required for verification
Combines detection, metadata review, web research, evidence capture, and handoff in one agent workflow.
Teams often switch between 3–6 tools to upload images, inspect metadata, search sources, document findings, and share results.
Cross-channel evidence consistency
Keeps image findings, source URLs, EXIF details, confidence notes, and reviewer decisions in a single record.
Results are commonly copied between tabs, spreadsheets, screenshots, and docs, increasing inconsistency risk.
Cost and usage limits
One platform subscription covers the verification workflow instead of separate detector, scraping, storage, and reporting tools.
Free tools often cap scans or omit APIs; paid usage can stack across multiple products as volume grows.
Learning curve and reporting
Guided agent flow produces a structured authenticity report that non-technical teams can review.
Users must learn each tool’s interface and manually assemble evidence into a usable report.
Примеры рабочих сценариев
Реальные промты, которые можно скопировать в агента выше.
Verify a Viral Image with a Free AI Image Detector
Act as an image verification analyst. I need to assess whether a viral image is AI-generated, manipulated, or likely authentic using free AI image detector options and manual verification steps. Context: The image is being shared widely on social media and may influence public opinion. Please create a practical verification workflow that includes: 1) which free AI image detector types or tools to try, 2) how to inspect metadata and EXIF data, 3) how to run reverse image searches, 4) how to interpret confidence scores without overclaiming, 5) how to document results for a public-facing fact-check, and 6) a final decision framework using labels such as likely authentic, inconclusive, likely AI-generated, or likely manipulated. Include cautions about false positives, false negatives, privacy, and upload retention policies.
A step-by-step viral image verification playbook that helps users combine free AI image detector results with metadata inspection, reverse image search, and cautious human judgment before publishing a conclusion.
Compare Free AI Image Detectors for a Small Newsroom
Act as a newsroom technology advisor. I need to choose the best free or freemium AI image detector workflow for a small journalism team that verifies images before publication. Compare detector profiles based on detection accuracy, daily free scan limits, batch upload support, metadata analysis, watermark or provenance detection, API availability, privacy policy, processing speed, and ease of use. Create a recommendation matrix, a testing plan using real photos, edited photos, and AI-generated images, and a standard operating procedure for reporters. Make the guidance practical for a team with limited budget and no dedicated forensic analyst.
A practical comparison and adoption guide for a small newsroom, including a detector evaluation matrix, benchmark testing plan, and repeatable image verification SOP for reporters and editors.
Create a Free AI Image Authenticity Check Workflow for Social Media Moderation
Act as a trust and safety operations designer. I manage a social media community and need a free AI image detector workflow to flag potentially synthetic or manipulated images before they spread misinformation. Design a lightweight moderation process that includes image intake, automated free detector checks, metadata review, reverse image search, suspicious-region analysis if available, escalation rules, user notification templates, and final moderation labels. Include thresholds for low, medium, and high risk; explain how moderators should handle inconclusive results; and provide a privacy-safe policy for image uploads and data retention.
A ready-to-use social media moderation workflow that uses free AI image detection, manual verification, escalation rules, and clear moderation labels to reduce misinformation risk while minimizing false accusations.
Справка
Другие инструменты в этой области
Отдельные решения, закрывающие часть этого сценария. Агент выше справляется со всеми ними в одном диалоге.