

Klyve
A free, local-first, desktop Automated Software Factory that uses any of OpenAI, Anthropic, Gemini, DeepSeek, custom or local LLM APIs to handle the full SDLC, from spec elaboration to coding and testing, without any cloud-based backend.
Features
Properties
- Privacy focused
Features
Git Support
- No registration required
- Extensible by Plugins/Extensions
- No Tracking
- Ad-free
- No Subscription
- Offline
- AI-Powered
Tags
- coding-assistant
- gemini-ai
- Artificial intelligence
- Developer Tools
- gemini
- local-first
- Freelancing
- sdlc
- Ollama
- anthropic
- free-apps
- Software developer
- deepseek-r1
- OpenAI
Klyve News & Activities
Recent activities
- mlinside added Klyve
mlinside added Klyve as alternative to Devin, Google Antigravity and Kiro
Klyve information
What is Klyve?
Klyve is a specialized software development process orchestrator for the OpenAI, Anthropic, Deep Seek, Gemini, custom, and locally (Ollama) hosted LLM APIs. It runs in a secure desktop environment and is designed to allow a single developer to engineer complete applications by automating the repetitive aspects of the SDLC.
The software distinguishes itself by handling the "process" of coding rather than just the syntax. It includes modules for specification refinement, architecture planning, coding, and automated regression testing. It produces and helps maintain formal project documentation, including plans, specs, reports, and records. It is also useful for "brownfield" or existing application maintenance and development, as it can ingest existing codebases to map their structure and create specifications before attempting modifications. It (optionally) integrates with Git, Jira and your IDE.
Privacy & Security: The application is built as a standalone desktop executable (Python/PySide6) and includes an internal "Iron Vault" mechanism to protect the orchestration logic, ensuring the integrity of the agent workflows. The local SQLite database is encrypted using SQLCipher, and the system follows a "Bring Your Own Key" (BYOK) model. No installation of Python or dependencies is required; the download is a self-contained environment. There is no cloud back end, and the application only submits snippets of specs or code to the LLM in order to generate the next output.









