PromptMatrix is an open-source prompt CI/CD pipeline and sub-5ms runtime governance control plane for AI agent swarms and LLM applications.
Stop hardcoding system instructions into config files or application repositories. PromptMatrix decouples prompt behavioral specifications from code executionโallowing product teams and engineers to version, evaluate, approve, and hot-patch prompts without ever triggering a 20-minute application redeployment.
โข โฑ๏ธ Zero-Downtime Hot Swaps: Update LLM instructions in real time with sub-5ms edge cache delivery. No Docker builds or container restarts.
โข โช Immutable Version Control: Git-like version history with line-by-line diff views and 1-click instant rollbacks.
โข โ๏ธ Automated Quality Gates: Built-in zero-dependency rule-based evaluations (<5ms offline) and LLM-as-a-judge scoring before merging to production.
โข ๐ฅ Team Governance: Non-engineers edit prompts visually; engineers review diffs and approve in 10 seconds.
โข ๐ก๏ธ Enterprise Security: Zero-trust BYOK architecture with AES-256-GCM encrypted evaluation keys and SHA-256 hashed API keys.
โข ๐ Universal Runtime Serve: Clean GET /pm/serve/{key} endpoint with dynamic {{variable}} interpolation.
๐ Flexible Deployment
โข Local-First (Community Edition): Runs locally on SQLite with zero external dependencies (MIT-licensed). โข Self-Hosted: Connects directly to your own PostgreSQL database. โข Managed Cloud: Scalable multi-tenant cloud control plane with automated eval gating and Slack bot integrations.
A startup from Guwahati, India that is founded by Jachin Saikia Sonowal.
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Systematic Prompt Exploration
PromptMatrix allows users to systematically test combinations of prompt variables, making it easier to identify which phrasing, structure, or parameters yield the best results across multiple AI use cases.
Time Efficiency
By automating the process of generating and testing multiple prompt variations, the tool saves significant time compared to manually crafting and testing each prompt individually.
Improved Consistency
The matrix-based approach helps ensure more consistent and reproducible results when experimenting with different prompt engineering strategies.
Useful for Research and Development
The tool is valuable for researchers and developers who need to benchmark prompt performance across different models or parameter sets in a structured way.
Accessible Interface
Being web-based and easy to access, PromptMatrix lowers the barrier to entry for experimenting with prompt engineering without requiring extensive coding knowledge.
Python, FastAPI, SQLAlchemy, Alembic, SQLite, PostgreSQL, Redis, PyJWT, Cryptography (AES-256-GCM), JavaScript, and Docker.
AI engineers, software development teams, and product managers building LLM applications, copilots, and multi-agent swarms who want to eliminate the 20-minute deployment cycle for prompt changes, prevent prompt drift, and give non-technical stakeholders a safe, governed environment to edit and evaluate prompts without breaking production.
PromptMatrix is a dedicated prompt CI/CD pipeline and runtime governance control plane purpose-built for AI agent swarms and LLM applications. It decouples prompt behavioral specifications from code execution, enabling teams to evaluate, approve, and hot-patch prompts in sub-5ms via edge caches without ever redeploying their application code. It offers built-in rule-based and LLM-as-a-judge quality gates, full Git-like versioning, and runs 100% local-first with zero external dependencies.
Unlike basic prompt CMS tools or complex cloud-locked observability suites, PromptMatrix provides: 1. Sub-5ms Runtime Serving: Hot-patch agent instructions in real time with zero application downtime. 2. True Local-First Freedom: Runs locally on SQLite (MIT licensed) with zero external database requirements. 3. Automated CI/CD Eval Gates: Blocks prompt regressions before they merge using both offline rule-based scoring and LLM-as-a-judge tests. 4. Seamless Multi-Agent Integration: Works natively with LangGraph, CrewAI, AutoGen, OpenClaw, and raw LLM APIs. 5. Zero-Trust Security: BYOK ephemeral evaluation execution and AES-256-GCM encrypted keys.
PromptMatrix was built out of necessity while running a 22-agent multi-agent swarm in production. Every time an agent's persona, briefing, or tool schema needed a minor wording tweak, an engineer had to hunt hardcoded strings across config files, open a pull request, wait for CI/CD builds, and restart the entire system. Recognizing that prompts are runtime behavioral specifications that require their own versioned control plane, the founder architected PromptMatrix to bridge product iteration with engineering reliability.
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