PromptCompose provides essential infrastructure for AI development with prompt versioning, A/B testing, and SDK integration. It transforms fragile text snippets into governed, scalable components, enabling teams to manage prompts with full audit trails, experiment with multiple versions, and deploy confidently through developer-friendly tools.
Free
How to use PromptCompose?
Start by drafting prompts in the smart editor with auto-complete for variables. Organize prompts into projects, apply reusable variable groups, and run A/B tests to compare performance. Once optimized, deploy prompts instantly via SDKs to production apps, ensuring consistent, data-driven outputs across your AI applications.
PromptCompose 's Core Features
Version Control for Prompts: Automatically tracks every change with complete history, side-by-side comparisons, and rollback capabilities for reliable prompt management.
A/B Testing Made Simple: Test multiple prompt versions in real-time, split traffic, measure engagement, and deploy winning variants based on performance data.
Developer-Ready SDKs: Lightweight SDKs for JavaScript and Python enable seamless integration, variable injection, and prompt management in your applications.
Multi-Project Hub: Manage multiple client accounts, products, or teams from a single interface, keeping prompts, variables, and tests organized and scalable.
Prompt Blueprints: Convert best-performing prompts into reusable templates, saving time and ensuring consistency across different projects and workflows.
Dynamic Variables: Insert personalized, data-driven values into prompts at scale, maintaining structure while adapting to real-time inputs for varied outputs.
Smart Editor: Built-in editor with auto-complete, keyword highlighting, and smart hints streamlines prompt writing, reducing errors and improving efficiency.
PromptCompose 's Use Cases
AI developers can version control prompts, track changes, and roll back updates, ensuring stable deployments in production environments without disruptions.
Marketing teams run A/B tests on promotional prompts to identify high-engagement variants, boosting campaign performance and customer interaction rates.
Startups use the multi-project hub to manage prompts for different client accounts, scaling AI services efficiently while maintaining organizational clarity.
Data scientists leverage dynamic variables to personalize AI responses based on user data, enhancing relevance in chatbots or recommendation systems.
Product managers deploy prompt blueprints across teams, standardizing workflows and accelerating development cycles for new AI features and updates.
Freelancers copy and reuse proven prompts and variable groups across projects, saving setup time and delivering consistent results to multiple clients.
