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Fileverity VS Deadpendency

Compare Fileverity VS Deadpendency and see what are their differences

Fileverity

Detect AI-generated and edited images and AI-written documents. Files are never retained, reports are traceable, and Enterprise runs on-premises, fully offline.

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Deadpendency

Automated software dependency project health tracking

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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Deadpendency seems to be more popular. It has been mentioned 2 times since March 2021.

social mentions
0 vs 2
Governance, Risk And Compliance popularity
100% vs 0%

Base details

Website, pricing, platforms and company facts side by side.

Fileverity
Deadpendency
Website fileverity.com deadpendency.com
Pricing
Official pricing
Official pricing
Company Startup from Canada · 10 - 19 employees · 2026 —
Listed in
AI Detection AI Detection Tool Fraud Detection And Prevention Fraud Detection InsurTech Governance, Risk And Compliance Auditing And Compliance Content Credentials Deepfake Detection AI AI Tools File Management +9
Dependency Management Software Development Security

About Fileverity and Deadpendency

In their own words, as submitted to SaaSHub.

Fileverity
Deadpendency

Fileverity checks whether an image was AI-generated or edited, and whether a PDF, Word or text file was written by AI. Image analysis locates edited regions to the pixel, reads Content Credentials (C2PA), watermarks and AI labels, and examines metadata in one check. Document analysis flags...

Read more about Fileverity

No description of Deadpendency yet.

Features and specs

What each product offers, as listed by its team.

Fileverity 8 features
Deadpendency 5 features
  • AI-generated image detection
    Tells you whether a photo was generated by AI, using Fileverity's own detection models across the major generator families. One check covers every major generator, not just one vendor's watermark.
  • Edited regions located to the pixel
    Pro analysis finds local edits such as AI inpainting, copy-move and retouching, and marks exactly where the image was changed. You get evidence you can point to, not just a score.
  • Content Credentials, watermarks and metadata
    Reads C2PA Content Credentials, AI labels, watermarks and EXIF metadata in the same check. Results are reported as recorded in the file, so reviewers can see what each signal does and does not show.
  • AI-written document detection
    Checks PDF, Word and text files for AI-written text in English, French, German, Spanish and Chinese. It flags the passages that drive the result by page or paragraph, and gives a recommended next step.
  • PDF metadata and edit history
    Every document report lists the creating and saving software, created and modified dates, and how many times the PDF was saved after creation. It also shows whether a digital signature is present.
  • Verifiable, timestamped reports
    Each report is bound to the exact file by its SHA-256 fingerprint and timestamped by DigiCert under RFC 3161. You get a sealed PDF and a JSON record, and anyone can confirm the report on a public verification page.
  • Files never retained
    Files are deleted as soon as the analysis is complete. Nothing is kept or used for training. The report keeps only a fingerprint and the findings.
  • Enterprise: API and on-premises deployment
    Volume pricing, API integration, custom risk policies and a data processing agreement. Fileverity can also run inside your own infrastructure, fully offline, for regulated teams in insurance, banking and legal.
  • Automated Dependency Monitoring
    Deadpendency automatically checks your project's dependencies for signs of being dead, unmaintained, or deprecated, saving developers from manually tracking the health of each dependency.
  • GitHub Integration
    Deadpendency integrates directly with GitHub as a GitHub App, making it easy to set up and run as part of your existing pull request and CI workflow without requiring additional infrastructure.
  • Early Warning System
    By catching dead or unmaintained dependencies early, Deadpendency helps teams avoid security risks and technical debt that come from relying on abandoned libraries.
  • Multi-Language Support
    Deadpendency supports a wide range of programming languages and package ecosystems, making it useful for polyglot projects and diverse development teams.
  • Low Configuration Overhead
    The tool is designed to work out of the box with minimal configuration, allowing teams to get value quickly without spending significant time on setup and customization.

Possible disadvantages

  • Limited to GitHub
    Deadpendency is primarily a GitHub App, which means teams using other platforms like GitLab or Bitbucket cannot easily use the service without switching or mirroring their repositories.
  • Potential False Positives
    The tool may flag dependencies as dead or unmaintained based on activity metrics, even when a library is stable and simply mature, leading to unnecessary concern or migration efforts.
  • Niche Use Case
    Dependency health checking is a relatively narrow function. Teams may prefer more comprehensive dependency management tools that also handle vulnerability scanning, license compliance, and version updates in one solution.
  • Reliance on External Signals
    Deadpendency relies on external signals like repository activity and release frequency to determine dependency health, which may not always accurately reflect the true maintenance status of a project.
  • Limited Community and Ecosystem
    As a relatively niche tool, Deadpendency has a smaller user community compared to alternatives like Dependabot or Renovate, which can mean fewer resources, community support, and third-party integrations.

Analysis

An editorial look at what each product does well and who it suits.

Fileverity
Deadpendency

No analysis of Fileverity yet.

Overall verdict

  • Deadpendency is a solid choice for teams needing automated dependency health monitoring, particularly for tracking deprecated, unmaintained, or archived packages that traditional vulnerability scanners often miss, integrating cleanly into CI workflows via GitHub Actions.

Why this product is good

  • Focuses specifically on dependency 'deadness' (deprecated, archived, unmaintained packages) rather than just security vulnerabilities, filling a gap left by tools like Dependabot
  • Simple integration as a GitHub Action, making it easy to add to existing CI/CD pipelines without heavy configuration
  • Provides clear, actionable reports that help developers proactively address technical debt before it becomes a security or maintenance liability
  • Supports multiple language ecosystems, offering broad applicability across different tech stacks
  • Lightweight and automated approach reduces manual auditing effort for dependency health

Recommended for

  • Development teams wanting to proactively manage technical debt in their dependency trees
  • Open source maintainers looking to keep their projects' dependencies healthy and current
  • Organizations using GitHub Actions for CI/CD who want an easy-to-integrate dependency health check
  • Security-conscious teams who want visibility into unmaintained packages that could pose future risks
  • Projects with many dependencies where manual tracking of deprecation status is impractical

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Fileverity
Deadpendency
100% 100%
Governance, Risk And Compliance
0% 0%
0% 0%
Software Development
100% 100%
100% 100%
Auditing And Compliance
0% 0%
0% 0%
Security
100% 100%

Questions & Answers

As answered by people managing Fileverity and Deadpendency.

Why should a person choose your product over its competitors?

Fileverity's answer

Evidence, not just a label. Edited regions are located to the pixel, and flagged passages are referenced by page or paragraph.

One check for many generators. It examines the content itself across the major model families, so you don't need a separate tool for each vendor's watermark.

Images and documents in one place. Check claim photos, receipts and documents in a single workflow, in five languages.

Reports you can file. Fingerprinted, timestamped and sealed reports that anyone can verify, even without Fileverity.

Privacy by design. Files are never retained or used for training, and on-premises deployment is available.

Pay per report. Start free, with no subscription.

What makes your product unique?

Fileverity's answer

Fileverity checks both images and documents, and every finding comes with a record that holds up when someone questions it. Instead of a single score, it shows where the evidence is: the edited region in a photo, or the AI-written passages in a document. It also reads Content Credentials (C2PA), watermarks, AI labels and file metadata in the same check. Each report is bound to the exact file by its SHA-256 fingerprint, timestamped by DigiCert under RFC 3161, sealed as a PDF and verifiable on a public page. Files are deleted after analysis and never used for training, and Enterprise customers can run Fileverity fully offline inside their own infrastructure.

How would you describe the primary audience of your product?

Fileverity's answer

Teams that have to decide whether a file can be trusted, and keep a record of why. That includes insurance claims handlers and anti-fraud (SIU) teams reviewing claim photos and documents, finance and expense teams checking receipts and invoices, legal and compliance teams, newsrooms and fact-checkers verifying images, and marketplaces and platforms reviewing user submissions. Individuals can also use the free checks to see whether an image is AI-generated or edited.

What's the story behind your product?

Fileverity's answer

Generative AI has made fabricated evidence look convincing. A fake damage photo, an AI-edited receipt or an AI-written claim letter no longer gives itself away through obvious mistakes. Most detection tools answer with a single score and keep the uploaded files, which doesn't work for teams whose decisions may later be challenged. Fileverity was built in Toronto by Entogo Inc. to close that gap. It runs on detection models built in-house, shows the evidence behind every finding, publishes its error rates, and issues a report that can be verified independently. The aim is to support human reviewers, not replace them.

Which are the primary technologies used for building your product?

Fileverity's answer

Proprietary detection models, including FVDOC V3 for AI-written documents

Image forensics for local edits, compression history and pixel consistency

C2PA Content Credentials and AI-label reading

SHA-256 file fingerprinting

RFC 3161 trusted timestamps from DigiCert

Sealed PDF reports with JSON data

User comments

Share your experience with using Fileverity and Deadpendency. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Fileverity 0 mentions
Deadpendency 2 mentions

Tracking Fileverity since Oct 2026.

  • Deadpendency Open Sourced
    I created a tiny startup in Haskell which failed RIP. I decided to open source the code though. Source: over 3 years ago
  • Twitch Streamers?
    I sometimes stream my Haskell work on deadpendency - https://www.twitch.tv/alistairbuzz. Source: over 5 years ago

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