PromptShuttle
Manage and render prompt templates and proxy LLM requests
About PromptShuttle
PromptShuttle makes it easy to prompt different LLMs, compare the results and collaborate on prompts, making it easier to try different LLMs and prompts in deployed applications. It proxies LLM API requests, reducing the burden of implementing different APIs and consolidating logs and invoices.
- Experiment: Try prompts against various LLMs, separate or in parallel, and compare the results.
- Collaborate: Track changes, add inline comments and collaborate on prompts with your team
- Deploy: Change active prompt versions and default LLMs per environment without code changes
- Prompt Templating: Template with
[[tokens]]and replace values in API calls with a simple{ "key": "value" }dictionary - Prompt Comments: Allow for inline comments with
/* C-Style */or// C++ Stylecomments for better collaboration and change tracking - Template Versions: Version each change to your prompt templates and track changes with a simple UI
What PromptShuttle does
AINave analysisRoute LLM API requests through a hosted proxy and run multi-agent workflows without writing agent logic in application code.
- Best for
- Platform teamsDevelopersAgenciesBusiness teams running AI workflows
- Use it to
- Proxying requests across multiple LLM providers
- Orchestrating multi-agent workflows server-side
- Comparing prompt and model results
- Tracking LLM costs and budgets per tenant or flow
- Managing prompt templates and versions
- Connecting an AI coding assistant to agent configuration
Show you're on AINave
Add the badge to PromptShuttle's site. It links back to this page.
Alternatives to PromptShuttle
See all 15 alternatives- 1
AnyApiAISame jobAI DevTool LLM Dev-Tools Chat
Pick it if you need one OpenAI SDK-compatible API for hundreds of models, with failover, budget alerts and a CLI, on macOS, Windows or Linux.
- 2
SpanlensOpen-source LLM observability: log cost, latency, tokens
Pick it if you mainly need open-source, self-hostable monitoring of cost, latency and nested agent traces, plus CI evaluations, rather than hosted orchestration.
- 3
CreateOSAI apps and agents in production.
Pick it if your product or enterprise team wants RAG pipelines and AI agent building with LLM routing and fallback, on a paid web platform.