Prompthub is a collaboration platform for prompt engineering teams to discover, manage, and deploy AI prompts. It offers Git-based versioning, prompt testing across multiple LLM providers, and automated evaluation pipelines. Users can deploy prompts via API, shareable forms, or Zapier integrations for seamless workflow integration.
Funding
Funding not disclosed
Founders
Product
Problem
Developing effective prompts for large language models (LLMs) requires iterative testing and comparison across different models and configurations. Managing and versioning these prompts, along with their outputs, can become complex and time-consuming, hindering prompt engineers' productivity. Existing solutions often lack collaborative features and the ability to seamlessly deploy prompts to various environments.
Solution
PromptHub is a collaborative prompt engineering platform that streamlines the creation, management, and deployment of AI prompts. The platform enables users to version control prompts, conduct batch testing, and compare outputs side-by-side across multiple LLMs. By providing a centralized workspace for prompt development, PromptHub eliminates the need for manual copy-pasting and spreadsheets. The platform also offers features for team collaboration, including merge requests and change tracking, ensuring consistency and alignment in prompt engineering efforts. Furthermore, PromptHub facilitates seamless deployment of prompts to various environments through API endpoints, shareable forms, and Zapier integration.
Target Audience
PromptHub targets prompt engineers, AI developers, and teams working on LLM-powered applications who need a collaborative platform to manage, test, and deploy prompts efficiently.
Features
- Version control for prompts with commit history and branching capabilities
- Batch testing functionality to evaluate prompt performance across different models, variables, and parameters
- Side-by-side output comparison for easy identification of optimal prompt configurations
- Support for various LLM providers, including OpenAI, Anthropic, Azure, Google, Meta, and Bedrock
- No-code prompt chaining for building complex LLM workflows
- Collaborative features such as merge requests and change tracking for team-based prompt engineering
- API endpoints for deploying prompts to applications and services
- Shareable forms for distributing prompts to end-users
- Zapier integration for connecting prompts to existing workflows
- Built-in templates for common prompt engineering tasks
- Monitoring dashboards for tracking request volume, costs, and latency