Build agents,
not plumbing.
Build the agent once, run it from Studio or code, and keep every prompt, tool call, model call, token, cost, and error in a trace you can debug.
What you get.
Version control for prompts
Treat prompts like product versions. Review changes, promote stable versions, and roll back when behavior regresses.
- +Version notes for prompt changes
- +Rollback to previous versions
- +Compare behavior before promotion
Full execution tracing
Debug AI workflows with visibility into prompts, model calls, tools, data queries, tokens, cost, and errors.
- +Span tree for every run
- +Token and cost breakdown
- +Inputs, outputs, latency, and errors
Hosted or BYO models
Use PromptRails-hosted models through the gateway or connect your own provider credentials at the workspace level.
- +Workspace-level provider credentials
- +Hosted model balance in Billing
- +Model settings per prompt version
Type-safe SDKs & CLI
Python, JavaScript, and Go SDKs for product integration, plus a CLI and MCP server for automation workflows.
- +Python, JS + Go SDKs with autocomplete
- +CLI for automation
- +MCP server and A2A protocol support
I/O schema validation
Define schemas for your prompts and agents. Enforce structure on inputs and outputs automatically.
- +JSON schema validation on inputs
- +Structured output enforcement
- +Jinja2 template engine for prompts
Agent orchestration patterns
Build simple agents, chains, multi-agent pipelines, or complex workflows with visual builders.
- +Simple, chain, workflow, and multi-agent patterns
- +Studio-based configuration
- +Memory, data, and tools in one agent view