Frequently Asked Questions
FAQ
Find answers to your questions about Decoder, including data privacy, AI use, security and more.
Trust Centre
How does Decoder ensure data privacy for your code?
Decoder ensures your code's privacy by performing all analyses entirely in memory. Uploaded files are processed in real-time and discarded immediately after analysis. No copies of your source code are stored, cached, or backed up. Analysis results, like mind maps and metrics, are stored for your convenience but contain no raw source code.
Do you follow industry best practices to keep my data safe?
We follow industry best practices to keep your data safe:
- Encrypted connections: All data transmitted between your browser and Decoder is encrypted using TLS/HTTPS.
- Access controls: Your analyses are private to your account and cannot be accessed by other users.
- No third-party sharing: Your code and analysis results are never shared with third parties.
- Secure authentication: User accounts are protected with securely hashed passwords.
How do you use AI and Data?
Decoder uses AI to generate insights about your code. Here is how we handle that responsibly:
- AI is used solely for analysis — generating documentation, mind maps, quality metrics, and recommendations.
- Your code is not used to train any AI or machine learning models.
- Analysis results and generated documentation belong entirely to you.
- AI processing happens on demand and code is not retained after the AI has produced its output.
Am I in control of my data?
You are always in control of your data within Decoder:
- Delete analyses: Remove any analysis and its generated results at any time from your dashboard.
- Manage your account: Update your profile or delete your account through account settings.
- Onboarding preferences: Choose whether to see the welcome guide on login.
- No lock-in: Your generated documentation and insights can be viewed and used as you see fit.
AI Code Analysis & Decoder
What is AI-powered code analysis?
AI-powered code analysis uses artificial intelligence to evaluate your codebase, providing insights into its structure, functionality, and areas for improvement.
Which languages and files can you analyse?
Supported coding languages and file types are as follows:
- Python: .py
- JavaScript: .js, .jsx, .ts, .tsx
- C/C++: .c, .cpp, .cc, .cxx, .h, .hpp
- C#: .cs
- Go: .go
- Java: .java
- Rust: .rs
- Kotlin: .kt
- Swift: .swift
- Web: .html, .htm, .css
- Others: .php, .rb
What is Decoder?
Decoder is an AI-powered codebase intelligence platform. It takes your existing source code and transforms it into clear architectural insights, visual maps, health scores, and professional documentation — without requiring any manual effort from your team.
What are the Key Features of Decoder?
1. Instant Codebase Understanding
Upload a ZIP or connect a GitHub repository and Decoder produces a full architectural breakdown in minutes — identifying functions, classes, API endpoints, design patterns, and dependencies automatically.
2. Visual Relationship Mapping
Interactive mind maps and dependency graphs let developers and architects see how modules and files connect to each other at a glance, rather than reading through thousands of lines of code.
3. Health Scoring
Every codebase gets scored across three dimensions — Maintainability, Scalability, and Testability — giving engineering leaders an objective baseline to track improvement over time.
4. Technical Debt in Business Terms
Decoder detects code smells, prioritises them by severity, and converts them into an estimated remediation cost in real dollars — so executives and product owners can make informed investment decisions without needing to be technical.
5. Automated Documentation
Generates up-to-date architecture, security, and onboarding documentation, exportable as DOCX, Markdown, or HTML. No more stale wikis.
6. System-Level Multi-Repo Analysis
Analyse groups of repositories together to understand cross-service dependencies, shared components, and architectural risks across an entire product ecosystem.
7. Team Collaboration & Access Control
Shared workspaces with role-based access (Admin / Reviewer) and an invite system, so the right people see the right information.
8. White-Label Ready
Decoder supports dynamic branding per client domain, making it suitable for agencies and consultancies to offer under their own brand.
What are Decoder's Key Benefits?
Why Decoder vs. Going Directly to OpenAI / Claude?
This is a fair question — Decoder uses GPT-4o under the hood, so why not just use an LLM directly?
1. You'd be building the product yourself
Pasting code into ChatGPT gives you a one-off conversation. Decoder gives you a structured, repeatable analysis pipeline with persistence, history, team access, and reporting. Building that yourself is a significant engineering investment.
2. Context limits and file handling
LLMs have token windows. Large real-world codebases span hundreds of files and hundreds of thousands of lines. Decoder handles ingestion, preprocessing, chunking, parallel analysis, and result aggregation — all the hard work that makes large codebases actually analysable.
3. Structured, consistent outputs
A raw LLM gives you a text response. Decoder gives you health scores, filterable smell lists, interactive graphs, ROI calculations, and exportable documents in standardised formats — immediately shareable with clients or leadership.
4. Visualisations
No LLM provider gives you an interactive dependency graph or mind map. Decoder renders D3.js-powered visuals that make complex codebases navigable.
5. Team collaboration, not individual prompting
LLMs are single-user chat interfaces. Decoder supports shared workspaces, role-based permissions, and invite-based collaboration — essential for any team or consultancy use case.
6. Security and provenance
Every analysis is stored, versioned, and attributable. You know who ran what, when, and on which codebase — something a chat interface cannot provide.
7. White-label and client delivery
Agencies and consultancies can present Decoder's output under their own brand. You cannot white-label ChatGPT.
In short: LLM providers give you a powerful engine. Decoder gives you the car — purpose-built for code intelligence, ready to drive.
Application Security
How does Decoder strengthen application security?
Decoder strengthens your application's security by conducting a comprehensive analysis to identify vulnerabilities and providing actionable solutions to mitigate risks effectively.
Code Quality
How does Decoder help you improve code quality?
Decoder helps you improve code quality by identifying code smells, recommending targeted improvements, and enhancing security. This ensures your code is clean, efficient, and reliable.
Legacy Code
Can Decoder handle legacy code?
Yes, Decoder is designed to analyze and improve even the most complex legacy codebases, offering actionable recommendations for modernization.
Payment Methods
What payment methods do you accept?
We accept credit cards, Apple Pay, and Google Pay for your convenience.