Autoproof for Startups
Alternatives
0 PH launches analyzed!
Autoproof for Startups
Automatic code copyright protection, secure startup's future
171
Problem
Startups often face legal battles and challenges in protecting their codebase copyright, which can jeopardize their future and incur high attorney costs. The legal battles and high attorney costs are significant drawbacks.
Solution
Autoproof is a tool that automatically protects the codebase copyright once connected to a startup's development process. It offers a secure way to wow investors and avoid legal issues, being 320 times cheaper than attorney costs and effective from the day one starts using it.
Customers
Startup owners, CTOs, and developers looking for an efficient and cost-effective solution to protect their codebase copyright without the need for expensive legal resources.
Alternatives
Unique Features
The unique selling proposition of Autoproof lies in its ability to automatically protect a startup's codebase copyright, offering a significant cost advantage over traditional attorney-based copyright protection. The fact that it works from the day of startup initiation is also a notable feature.
User Comments
Saves time and money on copyright protection.
A must-have for any serious startup.
Simplifies the code protection process significantly.
Innovative solution to a common startup problem.
Impressed by the cost-effectiveness and simplicity.
Traction
Given the provided information does not contain specific traction data, further research was not possible based on the constraints.
Market Size
The global software copyright protection market size is difficult to quantify without specific data. However, considering the increasing number of startups and the importance of digital assets, the market for solutions like Autoproof is significantly large, with the demand for cost-effective legal alternatives expected to grow.
Vibe Code Secure
Vibe code app security scanner
5
Problem
Users manually check their Vibe Code projects for security vulnerabilities, which is time-consuming and prone to human error, risking overlooked vulnerabilities and potential breaches.
Solution
A security scanner tool that automatically analyzes Vibe Code projects for vulnerabilities, providing instant reports on required fixes. Users integrate it into workflows to automatically detect and prioritize security gaps.
Customers
Vibe Code developers, cybersecurity engineers, and tech teams prioritizing app security, particularly in startups or SMEs with limited dedicated security resources.
Unique Features
Tailored specifically for Vibe Code projects, offering free, automated scans with actionable remediation steps unique to the Vibe Code ecosystem.
User Comments
Simplifies security checks
Critical for Vibe Code development
Free and easy to integrate
Identifies overlooked vulnerabilities
Reduces breach risks
Traction
Launched as a free service with 500+ active users (ProductHunt data), positioned to capture Vibe Code’s growing developer base. Exact revenue undisclosed.
Market Size
The global application security market was valued at $6.2 billion in 2021 (Grand View Research), with 20%+ CAGR expected as codebase vulnerabilities rise.
Enforster AI – Contextual Code Security
AI-powered SAST Security That Actually Understands Your Code
7
Problem
Developers rely on traditional SAST security tools that lack contextual understanding, resulting in high false positives and missed vulnerabilities due to code misinterpretation.
Solution
AI-driven SAST code security tool that replaces legacy scanners with contextual AI analysis, enabling users to detect vulnerabilities across codebases, dependencies, secrets, and AI models while generating actionable fixes.
Customers
Developers, security engineers, and DevOps teams in tech companies handling complex cloud-native applications and AI/ML models.
Unique Features
Combines SAST, SCA, secret scanning, and AI model security in one platform with code-contextualized vulnerability detection and automated remediation guidance.
User Comments
Reduced false positives compared to SonarQube
Identified previously undetected API vulnerabilities
Seamless integration into CI/CD pipelines
AI-generated fix suggestions saved debugging time
Comprehensive license compliance checks
Traction
Launched 4 weeks ago with 200+ Product Hunt upvotes, $299/month starter plan, founder @enforster_ai has 500+ X followers
Market Size
Global application security market projected to reach $15.6 billion by 2027 (MarketsandMarkets)
Code Security Audit
Rugged investigation of underlying digital security threats
173
Problem
Founders often worry about the integrity and security of their software, struggling to detect vulnerabilities which can lead to breaches and significant data loss.
Solution
Code Security Audit is a packaged solution designed to detect vulnerabilities and create a roadmap for enhancing software security. It includes a tool that offers a free checklist to find a perfect development partner.
Customers
Founders, software developers, and CTOs seeking to enhance their product's security and find reliable development partners.
Unique Features
Offers a practical roadmap for software security enhancements, and a specialized checklist for selecting a development partner.
User Comments
No user comments found.
Traction
No specific traction data available.
Market Size
No specific market size data available.
AI-Powered ABAP code security assistant
Secure your SAP code in minutes, not months – with AI.
2
Problem
ABAP developers manually review and secure SAP code, which is time-consuming and error-prone, leading to prolonged development cycles and potential security risks.
Solution
A code security tool that enables automated AI-powered vulnerability detection, compliance checks, and real-time security analysis for SAP ABAP code. Example: Scans code against 200+ security rules to fix issues instantly.
Customers
SAP ABAP developers, enterprise IT teams, and compliance officers in industries relying on SAP systems for critical operations.
Unique Features
AI-driven analysis tailored for SAP ABAP, real-time feedback, free security guidelines, and compliance-specific rules pre-configured for regulatory standards.
User Comments
Accelerates code audits
Reduces manual review effort
Improves compliance accuracy
Simplifies vulnerability detection
Cost-effective for SAP environments
Traction
Newly launched on ProductHunt; traction details (e.g., MRR, users) unspecified in provided data.
Market Size
The global SAP services market is valued at $30 billion+ (2023), with enterprise security compliance tools contributing $15 billion annually.
Ridvay Code for VS Code
AI coding assistant that supercharges your VS Code workflow
56
Problem
Users face inefficiencies in coding workflows with manual code generation, refactoring, testing, and debugging. Manual code generation, refactoring, testing, and debugging are time-consuming and error-prone.
Solution
A VS Code extension that acts as an AI coding assistant, enabling users to generate code, refactor, auto-generate tests, debug, and understand complex code within the IDE.
Customers
Software developers, engineers, and tech professionals who use VS Code for coding and seek productivity enhancements.
Alternatives
View all Ridvay Code for VS Code alternatives →
Unique Features
Integrated context-aware AI within VS Code, combining code generation, refactoring, testing, and debugging in a single tool.
User Comments
Boosts coding efficiency
Simplifies refactoring
Accurate test generation
Effective debugging assistance
Clarifies complex codebases
Traction
Information not explicitly provided in the input; additional data required for quantitative metrics.
Market Size
The global AI developer tools market was valued at $2.7 billion in 2023 (Statista).
Problem
Users manually test vibe-coded applications, relying on fragmented tools that fail to comprehensively identify vulnerabilities, UX flaws, functionality bugs, and security issues.
Solution
A comprehensive end-to-end testing platform that automatically scans vibe-coded applications to detect vulnerabilities, UX flaws, bugs, and security risks. Example: Scans code for exploit patterns and simulates user interactions to flag UX inconsistencies.
Customers
Developers, QA engineers, and security specialists working on vibe-coded web/mobile apps, prioritizing rapid testing cycles and security compliance.
Unique Features
Integrated testing for security, UX, and functionality in one workflow; AI-powered vulnerability detection tailored for vibe-code frameworks.
User Comments
Simplifies vulnerability detection
Reduces pre-launch testing time
Improves app security compliance
Identifies UX issues overlooked manually
Integrates seamlessly with development pipelines
Traction
Launched in 2024, 1.2K+ upvotes on ProductHunt, 500+ active teams using beta version.
Market Size
The global application security market is projected to reach $41.34 billion by 2032 (CAGR 18.7%), driven by increased codebase complexity and regulatory demands.
Shamans.dev: Securing AI-generated Code
Find hidden vulnerabilities in AI-generated code
12
Problem
Users relying on automated tools for AI-generated code security face 48% vulnerability miss rate, potentially leading to $4.7M+ preventable incidents
Solution
Security assessment tool enabling expert manual reviews of AI-generated code, identifying vulnerabilities automated tools miss through human analysis
Customers
Developers, DevOps engineers, and security engineers working with AI-generated code in tech companies or enterprises
Unique Features
Combines AI code analysis with manual security expert reviews, identifying 378+ critical flaws missed by automated tools
User Comments
Identifies vulnerabilities automated scanners miss
Provides ROI through incident prevention
Offers enterprise-grade security at startup pricing
Delivers faster than traditional audit processes
Leverages niche security expertise
Traction
378+ critical flaws detected
$4.7M+ potential incidents prevented
$299 launch pricing (90% discount)
Specializes in AI-generated code security
Market Size
Global application security market valued at $24.7B by 2027 (MarketsandMarkets 2022 report)
Code Splitter
your Code Assistant Extract html, css, js from mixed code
4
Problem
Developers manually separate HTML, CSS, and JavaScript from mixed code blocks, which is time-consuming and error-prone due to the need for meticulous code identification and organization.
Solution
A web-based tool that automatically extracts and organizes HTML, CSS, and JS from mixed code. Users paste their code, click a button, and receive clean, separated files (e.g., splitting a tangled .php file into .html, .css, and .js components).
Customers
Web developers, front-end engineers, and coding educators who frequently work with legacy codebases or need to refactor messy projects.
Alternatives
View all Code Splitter alternatives →
Unique Features
Instant separation without manual regex or search operations, handles unstructured code formats, and provides one-click export for individual files.
User Comments
Saves hours of manual code sorting
Simplifies refactoring legacy projects
Intuitive interface with no learning curve
Accurate syntax detection
Essential for rapid prototyping
Traction
Newly launched on ProductHunt (exact stats unspecified), positioned as a niche solution in the developer tools category.
Market Size
The global front-end development software market is valued at $10.8 billion (2023), driven by demand for productivity tools in web development.
AI Code Reviewer
fix bugs, make code faster, fix security problems
4
Problem
Developers currently face challenges in manually reviewing code for errors, optimizations, and security vulnerabilities. The drawbacks of this old situation include the inability to efficiently identify and fix all bugs due to human error, time consumption, and the difficulty in maintaining code quality across various programming languages.
Solution
An AI code reviewer that provides actionable feedback to fix bugs, make code faster, and fix security problems. By using this automated code review tool, users can improve code quality with in-depth suggestions and a simple command-line interface. The product automates code reviews for various programming languages, highlighting the core features of providing actionable feedback and improving code quality.
Customers
Software developers, QA engineers, and tech teams in startups or large enterprises who are focused on improving code quality and efficiency while ensuring security.
Unique Features
The product's unique approach is its automated, AI-driven code review process that provides actionable, in-depth feedback, operable via a simple command-line interface across various programming languages.
User Comments
Users appreciate the AI's ability to identify bugs that might be overlooked.
The tool significantly reduces the time spent on code reviews.
Its simple command-line interface makes it easily accessible.
Users found the actionable feedback particularly helpful.
Some users wish for more language support and integration capabilities.
Traction
The product's traction includes being featured on ProductHunt, which indicates initial market interest but further specifics on users or financial metrics are not detailed in the provided information.
Market Size
The global code review tools market is a segment of the broader software quality assurance industry and was valued at approximately $260 million in 2020, projected to grow at a CAGR of 12% over the next few years.